AfroTech logo and headshots of  Dela Agbemabiese, Justin Barry, Nashlie Sephus and Colby Wise.
With AfroTech World occurring this week, we asked some of the company's Black scientists what they consider some of the systemic issues limiting underrepresented minorities from being more involved in the technology industry. We heard from Dela Agbemabiese (lower left), a data scientist, Justin Barry (upper left), applied scientist, Nashlie Sephus (upper right), applied science manager, and Colby Wise (lower right), senior deep learning scientist.
Credit: Glynis Condon

Issues of racial, ethnic and gender diversity are on the agenda at AfroTech World

Amazon scientists provide insights on issues related to lack of involvement of underrepresented minorities in the technology industry.

As CNBC reported earlier this year, six years after initially disclosing diversity reports, major technology companies have made little progress in hiring more minorities, especially Black employees with science and technology skills.

This presents a series of ongoing challenges. According the US Bureau of Labor Statistics (BLS), nearly one-quarter of the country’s total economic output is produced by high-tech industries, and in 2017 BLS projected there would be more than 1 million job openings in computer and information technology over the next 10 years. Moreover, computing occupation salaries are more than twice the median wage for all other occupations, according to BLS.

“When we look at tech and its impact on our economy, and the simultaneous underrepresentation of the Black community, it is a critically important racial and economic justice issue," says Allison Scott, CEO of the Kapor Center. “When the tech workforce and leadership reflects the diverse experiences and backgrounds of our nation, I believe tech can begin to play an integral role in addressing long-standing disparities that exist in this country.”

As of December 31, 2019, Amazon reported that 26.5% of its global workforce identifies as Black/African American, 26.5% Asian, 18.5% Hispanic/Latinx, 1.3% as Native American, and 3.6% as two or more races.  The 26.5% of employees who identify as Black/African American work in both non-technical and technical roles.

This week at AfroTech World, issues related to the lack of adequate racial, ethnic, and gender diversity within the technology industry are on the agenda as leaders in technology and business come together to exchange ideas for creating greater opportunity for Blacks in technology.  Amazon is a Diamond Sponsor of this year’s event, and has a virtual recruiting booth.  

On Nov. 13, the company is hosting a virtual event, “Our Voices, Our Power”, presented by Amazon’s Black Employee Network (BEN) affinity group. Attendees will hear employees share their Amazon journey stories, learn about career opportunities, and enjoy entertainment.

In advance of AfroTech, Amazon Science asked some of the company’s Black scientists what they consider some of the systemic issues limiting underrepresented minorities’ involvement in the technology industry, about some of the issues they have had to overcome in pursuing their science careers, who or what inspired them to pursue their science careers, and what lessons we might take from their individual experiences. 

Dela Agbemabiese is a data scientist within Amazon’s advertising organization. He earned his master’s degree in business administration from Drexel University.

Dela Agbemabiese
Dela Agbemabiese

What do you consider some of the systemic issues limiting underrepresented minorities from greater employment opportunities in the technology industry?

Lack of financial resources to stimulate curiosity in tech, lack of mentors or heroes to look up to due to low representation, and societal prejudice hindering opportunities.

Lack of financial resources to stimulate curiosity in tech. I have been fortunate and blessed my entire life.  All gratitude goes to my parents. I was born in Ghana, West Africa. My mom was a nurse, and my dad an economist. Due to the nature of my dad’s work, I got the opportunity to travel a lot as a kid, got enrolled into a course at eight years old to get a Linux command line certificate, and always had access to tech resources. My parents sacrificed to ensure I attended the best schools, and there is not a single thing I ever asked for that I did not get. This may not be the case for all children, whose parents are possibly working hard doing multiple jobs, and in some cases are single parents. If the financial resources I had were similar to that of many minority children, it would be unlikely for me to be where I am today.

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Lack of mentors or heroes to look up to due to low representation. While my dad was heavy on econometrics and I learned a thing or two from him, it was my cousin Martey to whom I looked up. He was brilliant academically, and I always wanted to be like him. He tutored me in math and physics, thus giving me an edge over my classmates. Martey was not my only mentor, in fact, I had many, including Yao Obeng, who helped me nurture my creativity and problem-solving skills. Many minority children may not have mentors or heroes within tech to encourage and inspire interest in tech-related careers. If I did not have these mentors to motivate me, it would be unlikely for me to be where I am today.

Societal prejudice hindering opportunities. Growing up in Ghana, prejudice did not exist from a racial standpoint. Once I moved to the United States for my undergraduate degree, this became a reality. My minority friends and I have had to work twice as hard as our peers to prove we are as good as our credentials. We strived to invalidate stereotypes about minorities through the quality of our work and our work ethic. With everything I do, in the back of my mind I am thinking about how my actions or inactions affect the perception towards minorities: am I enabling some of these unfounded prejudices? Or am I, through my work, educating my peers and superiors? For me, this societal prejudice only began when I came to the United States for my undergraduate degree, but imagine the minority children out there who have had to live with this their entire lives. It sure can get demoralizing.

What are some of the obstacles you had to overcome in pursuing your science career?

Societal prejudice hindering opportunities. I have been lucky to have managers and peers that are inclusive and open-minded, that judge me based on the quality of my work. Rachel McKitrick was my first manager in Amazon. I joined Amazon as a business analyst, despite my previous role as a senior data scientist. I just wanted to join Amazon! Rachel knew my business analyst role was not ideal, and gave me projects that were science oriented, which ultimately enabled my transition to scientist. My second manager, Monica Wu, always made herself available to chat and made me feel like my voice and opinion mattered. My current team managed by Dauwe Vercamer and Andrew Petschek welcomed me with open arms, gave me opportunities to shine and lead within the team. They provide direct feedback that has made me a much better scientist today.

I have had the privilege of learning from a lot of people. Societal prejudice may be harder to solve for, but I believe a good place to start will be to find means for minority youth to gain access to some of the brilliant minds within the technology industry, be it through some virtual teaching programs, or through some mentoring programs. The prejudice may exist, the financial resources may be sparse or non-existent, but with heroes and mentors to look up to, a child’s imagination can be sparked for what could be.

Who or what inspired you to pursue your science career, and what lessons can we take from your experience?

My dad due to his econometrics background, and my childhood mentors who encouraged me to put math and science ahead of basketball and soccer. Since then, I have had lots of mentors along the way, especially here at Amazon. Individuals such as Leo Razoumov, Pranjal Mallick, Amy Ruschak, John Lafayette, and Oded Netzer, who have helped shape me into a better scientist.

My advice to Black students interested in a STEM career, or other Black scientists is to find mentors, and get them involved in your work. Meet with them once a week for even 10 minutes, and let them influence your work.

Justin Barry is an applied scientist with Amazon’s Prime Video organization. He earned his master’s degree in computer science from the University of Central Florida.

Justin Barry
Justin Barry

What do you consider some of the systemic issues limiting underrepresented minorities from greater employment opportunities in the technology industry?

This is a massive topic with a myriad of associated socioeconomic issues. One issue that jumps to the forefront for me is the schools where leading companies within the tech industry recruit from. Traditionally, these companies have limited their recruitment to top universities where Blacks and other underrepresented minorities comprise a small percentage of the student population. This is beginning to change, but I believe technology companies need to more aggressively expand their recruitment efforts, especially among historically Black colleges and universities (HBCUs).

What are some of the obstacles you had to overcome in pursuing your science career?

One issue is imposter syndrome — the idea that you're not good enough and you’re only in your position because you’ve been given special treatment. Although imposter syndrome is something everyone experiences, I think it’s particularly acute for Blacks given the clear underrepresentation within the technology industry. Imposter syndrome can touch all aspects of your job if you’re unaware, or if you don’t have the tools to deal with it. Not everyone has the tools to deal with it, and I suspect not everyone has correctly identified the problem.

Who or what inspired you to pursue your science career, and what lessons can we take from your experience?

Video games sparked my interest in computer science, and more specifically artificial intelligence. My undergraduate degree is in computer science and math, and machine learning and AI provide the opportunity to apply my computer science and math skills to real-world applications.

Nashlie Sephus is an applied science manager within Amazon Web Services Ai. She earned her PhD in electrical and computer engineering from Georgia Tech.

Nashlie Sephus
Nashlie Sephus

What do you consider some of the systemic issues limiting underrepresented minorities from greater employment opportunities in the technology industry?

Imposter syndrome is one issue I find common within underrepresented minority groups. It’s a feeling of being convinced that you don’t belong in the industry, or within advanced roles in the industry, regardless of your accolades and accomplishments. It is as if they are not real or didn’t happen. This is often due to not seeing many others who look like you in similar or higher positions. ‘You can’t be what you can’t see’ is a common thought. Also, there are few mentors or support systems for these groups, and as a black/female/engineer/scientist, you sometimes feel like the minority of the minority, which further isolates you.  

What are some of the obstacles you had to overcome in pursuing your science career?

At times, I have had to fight for myself and members of my teams for equal pay and advancement in my career. I also have needed to develop mechanisms to be heard when it was difficult to convey messages to those around me. I’m usually quiet and reserved, but over the years I’ve learned how to gain respect from peers by being more outspoken even, or especially, when I disagreed. This is one reason why I appreciate Amazon’s leadership principle: Have Backbone; Disagree and Commit. 

Who or what inspired you to pursue your science career, and what lessons can we take from your experience?

I grew up in a house full of women where we often did our own chores, like fixing and repairing things around the house. I was also always going to summer math and science camps in elementary and middle school, especially a summer engineering camp for girls after my eighth grade science teacher recommended I attend. This was when I was first introduced to the various areas of engineering, and fell in love with computer science. Being able to control the hardware with software was fascinating to me. I knew then that’s what I wanted to do. This early exposure to science was key to me figuring out one of my passions, in addition to music and sports.

Colby Wise is a senior deep learning scientist and manager within the AWS Machine Learning Solutions Lab. He earned his master’s degree in computer science from the Columbia University Fu Foundation School of Engineering and Applied Sciences.

Colby Wise
Colby Wise

What do you consider some of the systemic issues limiting underrepresented minorities from greater employment opportunities in the technology industry?

Educational opportunity. Science, technology, engineering, and math (STEM) careers in the technology industry are highly competitive. Over the years, we’ve seen advanced tools and technologies like cloud technology, machine learning, and deep learning, that were once reserved only for large companies or prestigious universities being utilized by students as early as junior high school. While this has created and accelerated educational opportunities for millions of students globally, the reality is that not all have been able to benefit. In the United States, public school funding varies significantly by geography, and where you grow up is a major factor in access to educational resources. Schools with advanced STEM courses and other after-school programs are valuable inroads for STEM students to accelerate their learning opportunities and explore careers in science. What’s more, these opportunities compound positively from lower educational levels to higher educational levels. While not the only factor, these programs are important when understanding the pipeline of underrepresented minorities in highly competitive industries like technology. For example, the US Federal Reserve conducted a study highlighting how educational attainment of parents plays an important role in children’s educational pursuits. Studies like this and others indicate that lower parental educational attainment may present a unique challenge for students. One potential consequence of underrepresentation of minorities in advanced degrees is that employment opportunities often arise from one’s social network, employee referrals, for example. This can be summarized as both an employment funnel problem and a network problem. While not always the case, a more diverse workforce can build connections to underrepresented talent pools. 

Financial equality. In a study from 2020, the US Federal Reserve found large and persistent gaps in net wealth and earnings by race and ethnicity. While education is a significant factor in wage gaps, the St. Louis Federal Reserve found net wealth by race was not as positively correlated with educational attainment for minorities. Educational attainment is extremely important. Many highly technical roles require advanced degrees. Financial equality and opportunity as characterized by job salary prospects, current income and net wealth, and access to educational funding sources like loans are all potential factors impacting lower minority employment. In 2016, the Brookings Institution found the median household net wealth for Black and Hispanic families to be 1/8th  that of white households. When you consider the rising cost of college and advanced degrees, this income and net wealth gap may also play a factor in why employment among underrepresented minorities is lower in highly competitive industries like technology. Specifically, minorities whose households cannot readily pay for advanced degrees choose between the implications of high debt burdens and lower comparative earnings, and often must forsake advanced degrees to enter or stay in the workforce.

Leadership representation. Representation of minorities in leadership positions is relatively low. It is unclear how much educational opportunity and financial equality contribute to this, compared to other issues such as equitable pathways to senior leadership positions. In many companies in which I have worked, you notice a similar triangular pattern of minority leadership where representation at junior levels is more in-line with industry trends, while there is a dearth of representation as you reach more senior positions. No doubt there is work to be done to drive greater employment of underrepresented minorities at all levels. But simply increasing the representation at entry levels does not address other attrition and talent-retention hurdles. Overall, companies need to take a more systematic, data-driven approach to move the needle and find solutions to underrepresentation of minorities in the tech industry. For instance, companies should not be afraid to tackle the complex issues at multiple hierarchies, such as creating innovative solutions to drive educational opportunity while objectively measuring current pathways to employment within the tech industry. Furthermore, companies should ensure financial equality by aligning corporate incentives with fair pay distributions, minority leadership representation, and talent development and retention.  

What are some of the obstacles you had to overcome in pursuing your science career?

Educational opportunity. While everyone’s path is different, unfortunately my story is rather common given its similarity to those of many underrepresented minorities. I faced and overcame obstacles in educational and financial opportunity plus roadblocks to leadership roles. I attribute my luck mainly to the many individuals who provided a helping hand, plus a little bit of hard work sprinkled in. I grew up in a single-parent household in an impoverished, high-crime inner-city area. Despite this, my family valued education highly, and one of my parents had an advanced degree which was extremely rare for the area. Given that, I always ranked in the top 1% in my coursework while very young. That said, district educational attainment rates were low, and advanced coursework or programs for gifted students were nonexistent. However, prior to high school an unfortunate family event led to me moving from one of the poorest areas in the country to one of the best school districts nationally. After discovering how far behind I was in math and science, my family and I worked extremely hard over several years to get me back in line with my expected academic grade level. Now fast-forwarding to college: I, like many other minorities, did not have the means to pay for college, nor easy access to loans. After being selected to a number of great schools, my decision was ultimately driven by the amount of money I received in scholarships and grants. During college I followed the same recipe for success: tons of luck, humility to ask for help, and a bit of hard work to land an internship as a sophomore at a prestigious Wall Street investment bank. There I was surrounded by some of the smartest minds in STEM, with many having achieved advanced degrees from top universities around the world. The vast majority of these individuals did not look like me. Desperately wanting to be accepted and succeed among my peers in industry is what drove me to pursue a career in science, and many years later brought me to AWS.

Who or what inspired you to pursue your science career, and what lessons can we take from your experience?

Family and friends. Ultimately, doing what you love and constantly learning while being curious is the greatest inspiration one needs to pursue a career in science. As discussed above, studies have shown a correlation between parental educational attainment and children’s attainment. Thinking forward a bit, I combined my passion for what I love in science — AI/ML — with a selfish goal of wanting to be a living model for a career in science for my children. My greatest inspiration, however, is my wife. She discovered her passion for science at a very young age with plentiful opportunities to explore that passion, ultimately helping her reach the pinnacles of academia, where she received undergraduate and graduate degrees from two of the top universities in the world. Her passion for science, hard work, and humility continue to inspire me on a daily basis.


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Job summaryAmazon Lab126 is an inventive research and development company that designs and engineers high-profile consumer electronics. Lab126 began in 2004 as a subsidiary of Amazon.com, Inc., originally creating the best-selling Kindle family of products. Since then, we have produced groundbreaking devices like Fire tablets, Fire TV, Amazon Echo and Halo.What will you help us create?Key job responsibilitiesYou will be part of a world-class Computer Vision team tasked with solving huge business problems through innovative technology and focus on product industrialization.We’ll need to tackle problems that span a variety of domains: computer vision, image recognition, machine learning, real-time and distributed systems. Everyone on the team needs to be entrepreneurial, wear many hats and work in a highly collaborative environment that’s more startup than big company.Major responsibilities:· Research, design, implement and evaluate novel computer vision algorithms· Work on large-scale datasets, focusing on creating scalable and accurate computer vision systems in versatile application fields· Collaborate closely with team members on developing systems from prototyping to production level· Collaborate with teams spread all over the world· Work closely with software engineering teams to drive scalable, real-time implementations· Track general business activity and provide clear, compelling management reports on a regular basis
US, MN, Minneapolis
Job summaryMachine learning (ML) has been strategic to Amazon from the early years. We are pioneers in areas such as recommendation engines, product search, eCommerce fraud detection, and large-scale optimization of fulfillment center operations.The Amazon ML Solutions Lab team helps AWS customers accelerate the use of machine learning to solve business and operational challenges and promote innovation in their organization. We are looking for a passionate, talented, and inventive Applied Scientist with a strong machine learning background to help develop solutions by pushing the envelope in Time Series, Automatic Speech Recognition (ASR), Natural Language Understanding (NLU), Machine Learning (ML) and Computer Vision (CV).As a ML Solutions Lab Applied Scientist, you are proficient in designing and developing advanced ML models to solve diverse challenges and opportunities. You will be working with terabytes of text, images, and other types of data and develop novel models to solve real-world problems. You'll design and run experiments, research new algorithms, and find new ways of optimizing risk, profitability, and customer experience. You will apply classical ML algorithms and cutting-edge deep learning (DL) and reinforcement learning approaches to areas such as drug discovery, customer segmentation, fraud prevention, capacity planning, predictive maintenance, pricing optimization, call center analytics, player pose estimation, event detection, and virtual assistant among others.The primary responsibilities of this role are to:· Design, develop, and evaluate innovative ML/DL models to solve diverse challenges and opportunities across industries· Interact with customer directly to understand their business problems, and help them with defining and implementing scalable ML/DL solutions to solve them· Work closely with account teams, research scientist teams, and product engineering teams to drive model implementations and new algorithmsThis position requires travel of up to 25%.About UsInclusive Team CultureHere at AWS, we embrace our differences. We are committed to furthering our culture of inclusion. We have ten employee-led affinity groups, reaching 40,000 employees in over 190 chapters globally. We have innovative benefit offerings, and host annual and ongoing learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences. Amazon’s culture of inclusion is reinforced within our 14 Leadership Principles, which remind team members to seek diverse perspectives, learn and be curious, and earn trust.Work/Life BalanceOur team puts a high value on work-life balance. It isn’t about how many hours you spend at home or at work; it’s about the flow you establish that brings energy to both parts of your life. We believe striking the right balance between your personal and professional life is critical to life-long happiness and fulfillment. We offer flexibility in working hours and encourage you to find your own balance between your work and personal lives.This position involves on-call responsibilities, typically for one week every two months. We don’t like getting paged in the middle of the night or on the weekend, so we work to ensure that our systems are fault tolerant. When we do get paged, we work together to resolve the root cause so that we don’t get paged for the same issue twice.Mentorship & Career GrowthOur team is dedicated to supporting new members. We have a broad mix of experience levels and tenures, and we’re building an environment that celebrates knowledge sharing and mentorship. Our senior members enjoy one-on-one mentoring and thorough, but kind, code reviews. We care about your career growth and strive to assign projects based on what will help each team member develop into a better-rounded engineer and enable them to take on more complex tasks in the future.
US, WA, Bellevue
Job summaryAmazon AI is looking for world class scientists to join its AI Lab. This group is entrusted with developing core machine learning algorithms for AWS. As a part of the AI Lab you will invent, implement, and deploy state of the art machine learning algorithms and systems. You will build prototypes and explore novel solutions to new problems at scale. You will interact closely with our customers and with the academic community. You will be at the heart of a growing and exciting focus area for AWS and work with other acclaimed engineers and world famous scientists.About UsInclusive Team CultureHere at AWS, we embrace our differences. We are committed to furthering our culture of inclusion. We have ten employee-led affinity groups, reaching 40,000 employees in over 190 chapters globally. We have innovative benefit offerings, and host annual and ongoing learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences. Amazon’s culture of inclusion is reinforced within our 14 Leadership Principles, which remind team members to seek diverse perspectives, learn and be curious, and earn trust.Work/Life BalanceOur team puts a high value on work-life balance. It isn’t about how many hours you spend at home or at work; it’s about the flow you establish that brings energy to both parts of your life. We believe striking the right balance between your personal and professional life is critical to life-long happiness and fulfillment. We offer flexibility in working hours and encourage you to find your own balance between your work and personal lives.Mentorship & Career GrowthOur team is dedicated to supporting new members. We have a broad mix of experience levels and tenures, and we’re building an environment that celebrates knowledge sharing and mentorship. Our senior members enjoy one-on-one mentoring and thorough, but kind, code reviews. We care about your career growth and strive to assign projects based on what will help each team member develop into a better-rounded engineer and enable them to take on more complex tasks in the future.
US, IL, Chicago
Job summaryMachine learning (ML) has been strategic to Amazon from the early years. We are pioneers in areas such as recommendation engines, product search, eCommerce fraud detection, and large-scale optimization of fulfillment center operations.The Amazon ML Solutions Lab team helps AWS customers accelerate the use of machine learning to solve business and operational challenges and promote innovation in their organization. We are looking for a passionate, talented, and inventive Applied Scientist with a strong machine learning background to help develop solutions by pushing the envelope in Time Series, Automatic Speech Recognition (ASR), Natural Language Understanding (NLU), Machine Learning (ML) and Computer Vision (CV).As a ML Solutions Lab Applied Scientist, you are proficient in designing and developing advanced ML models to solve diverse challenges and opportunities. You will be working with terabytes of text, images, and other types of data and develop novel models to solve real-world problems. You'll design and run experiments, research new algorithms, and find new ways of optimizing risk, profitability, and customer experience. You will apply classical ML algorithms and cutting-edge deep learning (DL) and reinforcement learning approaches to areas such as drug discovery, customer segmentation, fraud prevention, capacity planning, predictive maintenance, pricing optimization, call center analytics, player pose estimation, event detection, and virtual assistant among others.The primary responsibilities of this role are to:· Design, develop, and evaluate innovative ML/DL models to solve diverse challenges and opportunities across industries· Interact with customer directly to understand their business problems, and help them with defining and implementing scalable ML/DL solutions to solve them· Work closely with account teams, research scientist teams, and product engineering teams to drive model implementations and new algorithmsThis position requires travel of up to 25%.About UsInclusive Team CultureHere at AWS, we embrace our differences. We are committed to furthering our culture of inclusion. We have ten employee-led affinity groups, reaching 40,000 employees in over 190 chapters globally. We have innovative benefit offerings, and host annual and ongoing learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences. Amazon’s culture of inclusion is reinforced within our 14 Leadership Principles, which remind team members to seek diverse perspectives, learn and be curious, and earn trust.Work/Life BalanceOur team puts a high value on work-life balance. It isn’t about how many hours you spend at home or at work; it’s about the flow you establish that brings energy to both parts of your life. We believe striking the right balance between your personal and professional life is critical to life-long happiness and fulfillment. We offer flexibility in working hours and encourage you to find your own balance between your work and personal lives.This position involves on-call responsibilities, typically for one week every two months. We don’t like getting paged in the middle of the night or on the weekend, so we work to ensure that our systems are fault tolerant. When we do get paged, we work together to resolve the root cause so that we don’t get paged for the same issue twice.Mentorship & Career GrowthOur team is dedicated to supporting new members. We have a broad mix of experience levels and tenures, and we’re building an environment that celebrates knowledge sharing and mentorship. Our senior members enjoy one-on-one mentoring and thorough, but kind, code reviews. We care about your career growth and strive to assign projects based on what will help each team member develop into a better-rounded engineer and enable them to take on more complex tasks in the future.
US, TX, Austin
Job summaryMachine learning (ML) has been strategic to Amazon from the early years. We are pioneers in areas such as recommendation engines, product search, eCommerce fraud detection, and large-scale optimization of fulfillment center operations.The Amazon ML Solutions Lab team helps AWS customers accelerate the use of machine learning to solve business and operational challenges and promote innovation in their organization. We are looking for a passionate, talented, and inventive Applied Scientist with a strong machine learning background to help develop solutions by pushing the envelope in Time Series, Automatic Speech Recognition (ASR), Natural Language Understanding (NLU), Machine Learning (ML) and Computer Vision (CV).As a ML Solutions Lab Applied Scientist, you are proficient in designing and developing advanced ML models to solve diverse challenges and opportunities. You will be working with terabytes of text, images, and other types of data and develop novel models to solve real-world problems. You'll design and run experiments, research new algorithms, and find new ways of optimizing risk, profitability, and customer experience. You will apply classical ML algorithms and cutting-edge deep learning (DL) and reinforcement learning approaches to areas such as drug discovery, customer segmentation, fraud prevention, capacity planning, predictive maintenance, pricing optimization, call center analytics, player pose estimation, event detection, and virtual assistant among others.The primary responsibilities of this role are to:· Design, develop, and evaluate innovative ML/DL models to solve diverse challenges and opportunities across industries· Interact with customer directly to understand their business problems, and help them with defining and implementing scalable ML/DL solutions to solve them· Work closely with account teams, research scientist teams, and product engineering teams to drive model implementations and new algorithmsThis position requires travel of up to 25%.About UsInclusive Team CultureHere at AWS, we embrace our differences. We are committed to furthering our culture of inclusion. We have ten employee-led affinity groups, reaching 40,000 employees in over 190 chapters globally. We have innovative benefit offerings, and host annual and ongoing learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences. Amazon’s culture of inclusion is reinforced within our 14 Leadership Principles, which remind team members to seek diverse perspectives, learn and be curious, and earn trust.Work/Life BalanceOur team puts a high value on work-life balance. It isn’t about how many hours you spend at home or at work; it’s about the flow you establish that brings energy to both parts of your life. We believe striking the right balance between your personal and professional life is critical to life-long happiness and fulfillment. We offer flexibility in working hours and encourage you to find your own balance between your work and personal lives.This position involves on-call responsibilities, typically for one week every two months. We don’t like getting paged in the middle of the night or on the weekend, so we work to ensure that our systems are fault tolerant. When we do get paged, we work together to resolve the root cause so that we don’t get paged for the same issue twice.Mentorship & Career GrowthOur team is dedicated to supporting new members. We have a broad mix of experience levels and tenures, and we’re building an environment that celebrates knowledge sharing and mentorship. Our senior members enjoy one-on-one mentoring and thorough, but kind, code reviews. We care about your career growth and strive to assign projects based on what will help each team member develop into a better-rounded engineer and enable them to take on more complex tasks in the future.
US, MI, Detroit
Job summaryMachine learning (ML) has been strategic to Amazon from the early years. We are pioneers in areas such as recommendation engines, product search, eCommerce fraud detection, and large-scale optimization of fulfillment center operations.The Amazon ML Solutions Lab team helps AWS customers accelerate the use of machine learning to solve business and operational challenges and promote innovation in their organization. We are looking for a passionate, talented, and inventive Applied Scientist with a strong machine learning background to help develop solutions by pushing the envelope in Time Series, Automatic Speech Recognition (ASR), Natural Language Understanding (NLU), Machine Learning (ML) and Computer Vision (CV).As a ML Solutions Lab Applied Scientist, you are proficient in designing and developing advanced ML models to solve diverse challenges and opportunities. You will be working with terabytes of text, images, and other types of data and develop novel models to solve real-world problems. You'll design and run experiments, research new algorithms, and find new ways of optimizing risk, profitability, and customer experience. You will apply classical ML algorithms and cutting-edge deep learning (DL) and reinforcement learning approaches to areas such as drug discovery, customer segmentation, fraud prevention, capacity planning, predictive maintenance, pricing optimization, call center analytics, player pose estimation, event detection, and virtual assistant among others.The primary responsibilities of this role are to:· Design, develop, and evaluate innovative ML/DL models to solve diverse challenges and opportunities across industries· Interact with customer directly to understand their business problems, and help them with defining and implementing scalable ML/DL solutions to solve them· Work closely with account teams, research scientist teams, and product engineering teams to drive model implementations and new algorithmsThis position requires travel of up to 25%.About UsInclusive Team CultureHere at AWS, we embrace our differences. We are committed to furthering our culture of inclusion. We have ten employee-led affinity groups, reaching 40,000 employees in over 190 chapters globally. We have innovative benefit offerings, and host annual and ongoing learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences. Amazon’s culture of inclusion is reinforced within our 14 Leadership Principles, which remind team members to seek diverse perspectives, learn and be curious, and earn trust.Work/Life BalanceOur team puts a high value on work-life balance. It isn’t about how many hours you spend at home or at work; it’s about the flow you establish that brings energy to both parts of your life. We believe striking the right balance between your personal and professional life is critical to life-long happiness and fulfillment. We offer flexibility in working hours and encourage you to find your own balance between your work and personal lives.This position involves on-call responsibilities, typically for one week every two months. We don’t like getting paged in the middle of the night or on the weekend, so we work to ensure that our systems are fault tolerant. When we do get paged, we work together to resolve the root cause so that we don’t get paged for the same issue twice.Mentorship & Career GrowthOur team is dedicated to supporting new members. We have a broad mix of experience levels and tenures, and we’re building an environment that celebrates knowledge sharing and mentorship. Our senior members enjoy one-on-one mentoring and thorough, but kind, code reviews. We care about your career growth and strive to assign projects based on what will help each team member develop into a better-rounded engineer and enable them to take on more complex tasks in the future.
US, WA, Seattle
Job summaryAre you passionate about big data and machine learning? Do you enjoy solving complex analytical problems, build predictive analytics models and develop insights and recommendations at web scale? Do you want to make an impact in Amazon’s multi-billion-dollar Messaging business? Amazon’s Outbound Communication Services, OCS, owns foundational systems that power all of Amazon's customer-facing communication on Email, SMS, Push channels, and other emerging messaging applications. In 2020, we sent over 100 billion messages to our global customers on these channels! OCS builds self-governing and message-optimizing engines that leverage integrated Machine Learning, massive data processing and adaptive algorithms to deliver the best messages to Amazon’s customers, over the best channel, and at the right time. Our systems ensure best-in-class engagement experience, which spans transactional and marketing communications. We're building a top-notch team of engineers, applied scientists, data engineers, and engineering leaders. The problems we face are complex and interesting including information engineering, data mining of Big Data sets, and governing real-time messages at scale. We build large scale, distributed systems using multiple AWS services that we designed from the ground up.We are looking for a strong Applied Scientist to work backwards from customers, create models and develop insights, deliver impact, and drive growth of the OCS worldwide. As a Senior Applied Scientist on our team, you will be working with business stakeholders, product/program managers, developers and executives to deeply understand customer problems and priorities. You will form hypotheses, analyze the corpus of Outbound and Amazon data using statistical methods, build predictive models, generate recommendations to address a range of problems to optimize the value of the messages we send to our customers. These span developing insights on customer engagement trends, building models to inform message rates, channel selection, and defining segmentation for marketing, etc. Your expertise will enable us to enable new customer experiences while maintaining best-in-class customer experience. You will be comfortable with big data systems, intimately familiar with advanced machine learning and statistical methods, and experienced in applying these to solve business problems. You will have a strong bias towards customer obsession and delivering results while dealing with ambiguity in fast-paced dynamic environments.Roles and Responsibilities· Work with business teams, product/program managers, engineers and leadership to identify and prioritize customer and business problems· Translate these problems into specific analytical questions and form hypotheses that can be answered with available data using statistical methods or identify additional data needed in the master datasets to fill any gaps· Perform hand-on data analyses and modeling with huge datasets to develop insights and recommendations to inform decisions across the program· Design and run A/B experiments to validate the hypotheses and evaluate the impact of your optimizations and communicate your results to various stakeholders· Collaborate with engineers and product managers to build scalable solutions and new capabilities· Help on projects of high visibility across the organization and deliver business impact
US, MA, Cambridge
Job summaryThe Alexa Artificial Intelligence (AI) team is looking for a passionate, talented, and inventive Applied Scientist with a strong machine learning background to help build industry-leading Speech and Language technology. Our mission is to push the envelope in Automatic Speech Recognition (ASR), Natural Language Understanding (NLU), and Audio Signal Processing, in order to provide the best-possible experience for our customers.Key job responsibilitiesAs an Applied Scientist, you will work with talented peers to develop novel algorithms and modeling techniques to advance the state of the art in spoken language understanding. Your work will directly impact our customers in the form of products and services that make use of speech and language technology. You will leverage Amazon’s heterogeneous data sources and large-scale computing resources to accelerate advances in spoken language understanding.
US, WA, Bellevue
Job summaryAmazon’s Modeling and Optimization Team is looking for a senior science leader (Principal Research Scientist) to drive the development and optimization of the most complex transportation and fulfillment network in the world.The team is responsible for optimizing the global transportation and fulfillment network for Amazon.com and ensuring that the company is able to deliver our customers’ products to them as quickly, accurately, and cost effectively as possible. We design the network that delivers packages from fulfillment centers (FCs) to end customers, through both Amazon’s internal network as well as external partners, using ground and air methods. Optimizing these package flows requires designing the structure and operating parameters of the network, optimizing operations such as linehaul movements and sortation scheduling, and making the right capital investments in technology, buildings and equipment. It also requires partnering with peer research and product teams that drive inventory placement, selection, and forecasting, and incorporating information and algorithmic interfaces with those systems.We are seeking an experienced multi-disciplinary science leader, to lead the science development on projects in both developing algorithmic tools and driving long-term network strategy. In this role, you will work with and advise other research scientists in the team, develop your own scientific approaches, and partner with software and product teams as they deploy algorithmic solutions to our stakeholders. You will also partner with business leaders on projects that evaluate long-term strategic network choices, and present strategy papers to our senior-most leaders to drive long-term impact.To accomplish this, we expect you to have a strong research background in at least one of the following disciplines: operations research, computer science, operations management, statistics, or applied mathematics. You should also have business domain knowledge in transportation and distribution operations, along with some knowledge of inventory management theory and practice. You should have a strong publication record that demonstrates technical depth as well as consideration of practical aspects in your work. Experience partnering with companies on high-stakes R&D or consulting is a plus, but not a necessity.
US, VA, Arlington
Job summaryInterested in machine learning and AI? Can you envision a future where technology is driven primarily by smarter machines?The mission of AWS AI is to make machine learning easy, fast, and universal across all of our customers. Our world class platform provides the services that runs 85% of all on-cloud machine learning through performance optimizations, machine learning tools, and SDKs to democratize machine learning. Our customers include scientists, data analysts, and ML engineers all building and deploying models through either SageMaker or self-managed instances on EC2/EKS.The AWS Machine Learning Services group in Amazon AI is seeking applicants for an applied scientist position in the areas of fairness, bias, explainability, privacy, and model understanding in ML. As an applied scientist in AWS AI, you will be driving many scientific breakthroughs to help our customers understand and trust ML-based outcomes, and also working with software engineers to deploy these solutions to AWS customers. You will be working on the ML platforms and services that power over 85% of machine learning in the cloud, and help make machine learning fast, accessible, universal, and trustworthy for all our customers.We look for candidates with PhD in a relevant technical field (such as Algorithms, Machine Learning, AI, and Mathematics), preferably with interest / experience in explainability, fairness, privacy, and model understanding. We also encourage graduating PhD students as well as recent PhD graduates to apply. You will be working closely with software engineers so experience with cloud systems is a benefit. Our customers are deeply technical and the solutions we build for them are strongly coupled to technical feasibility. You must be able to thrive and succeed in an entrepreneurial environment, and not be hindered by ambiguity or competing priorities. This means you are not only able to develop and drive high-level strategic initiatives, but can also roll up your sleeves, dig in and get the job done. Ownership, high judgment, negotiation skills, ability to influence, analytical talent and leadership are essential to success in this role.For more information about AWS AI team, please see https://aws.amazon.com/machine-learning and https://aws.amazon.com/sagemaker.About UsInclusive Team CultureHere at AWS, we embrace our differences. We are committed to furthering our culture of inclusion. We have ten employee-led affinity groups, reaching 40,000 employees in over 190 chapters globally. We have innovative benefit offerings, and host annual and ongoing learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences. Amazon’s culture of inclusion is reinforced within our 14 Leadership Principles, which remind team members to seek diverse perspectives, learn and be curious, and earn trust.Work/Life BalanceOur team puts a high value on work-life balance. It isn’t about how many hours you spend at home or at work; it’s about the flow you establish that brings energy to both parts of your life. We believe striking the right balance between your personal and professional life is critical to life-long happiness and fulfillment. We offer flexibility in working hours and encourage you to find your own balance between your work and personal lives.Mentorship & Career GrowthOur team is dedicated to supporting new members. We have a broad mix of experience levels and tenures, and we’re building an environment that celebrates knowledge sharing and mentorship. Our senior members enjoy one-on-one mentoring. We care about your career growth and strive to assign projects based on what will help each team member develop into a better-rounded engineer and enable them to take on more complex tasks in the future.
LU, Luxembourg
Job summaryWould you like to pioneer new technologies in machine learning while leveraging Amazon's heterogenous data sources and large-scale computing resources?As a data scientist, your work will help Amazon raise the bar on customer obsession by providing our Sellers with the best customized experiences.We are looking for a passionate, talented, and inventive Scientist with a strong machine learning background to join us to build industry-leading technology.The ideal candidate will have extensive experience in Science work, business analytics and have the aptitude to incorporate new approaches and methodologies while dealing with ambiguities in sourcing processes. Excellent business and communication skills are a must to develop and define key business questions and to build data sets that answer those questions. You should have a demonstrated ability to think strategically and analytically about business, product, and technical challenges. Further, you must have the ability to build and communicate compelling value propositions, and work across the organization to achieve consensus. This role requires a strong passion for customers, a high level of comfort navigating ambiguity, and a keen sense of ownership and drive to deliver results.
US, WA, Seattle
Come join the AWS Marketplace Team in our mission to change the way enterprise software is bought and sold! AWS Marketplace enables software sellers to reach all AWS customers, and it enables software buyers to easily discover, purchase and consume software. Our goals include enriching the platform to support more diverse selection, improving buyer and seller experience, and supporting co-sell opportunities between AWS and our partners. Our vision is to make AWS Marketplace the one stop shop for buying and selling software - we're building the app store for AWS.A day in the lifeIn this role, you’ll be utilizing your creative and critical problem solving skills to drive new projects from ideation to implementation. You will improve and innovate on existing high impact analytical projects. Your outputs will focus on our team’s critical goals and help influence decision makers.About the hiring groupAbout UsInclusive Team CultureHere at AWS, we embrace our differences. We are committed to furthering our culture of inclusion. We have ten employee-led affinity groups, reaching 40,000 employees in over 190 chapters globally. We have innovative benefit offerings, and host annual and ongoing learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences. Amazon’s culture of inclusion is reinforced within our 16 Leadership Principles, which remind team members to seek diverse perspectives, learn and be curious, and earn trust.Work/Life BalanceOur team puts a high value on work-life balance. It isn’t about how many hours you spend at home or at work; it’s about the flow you establish that brings energy to both parts of your life. We believe striking the right balance between your personal and professional life is critical to life-long happiness and fulfillment. We offer flexibility in working hours and encourage you to find your own balance between your work and personal lives.Mentorship & Career GrowthOur team is dedicated to supporting new members. We have a broad mix of experience levels and tenures, and we’re building an environment that celebrates knowledge sharing and mentorship. We care about your career growth and strive to assign projects based on what will help each team member develop into a better-rounded professional and enable them to take on more complex tasks in the future.Job responsibilitiesWe are looking for a Data Scientist to join our rapidly growing Seattle team. As a Data Scientist, you are able to use a range of data science methodologies to solve challenging business problems when the solution is unclear. You have a combination of business acumen, broad knowledge of statistics, deep understanding of ML algorithms, and an analytical mindset. You thrive in a collaborative environment, and are passionate about learning. Our team utilizes a variety of AWS tools such as Redshift, Sagemaker, Lambda, S3, and EC2 with a variety of skillsets in Tabular ML, NLP, Forecasting, Probabilistic ML and Causal ML. You will bring knowledge in many of these domains along with your own specialties and skillsets.
DE, BE, Berlin
Machine Learning (ML) has been strategic to Amazon from the early years. We are pioneers in areas such as recommendation engines, product search, eCommerce fraud detection, and large-scale optimization of fulfillment center operations.Machine Learning University’s (MLU) mission is to teach people to apply ML to business and operational challenges. In service of this goal, we are growing our presence outside the US, and are looking to hire in EMEA region. We believe strongly that a practical knowledge of ML can be taught broadly, and is a key skill for many builders to learn. Come join Amazon’s Machine Learning University and help spread knowledge of ML!We have built a team of passionate science educators with the demonstrated ability to explain ML to an audience of technical professionals, enhance curriculum, and collaborate with scientists across the company. You will teach practitioners how to train, tune, and deploy ML models to solve challenges in customer segmentation, fraud prevention, capacity planning, predictive maintenance, pricing optimization, call center analtyics, and event detection among others. Practical experience with machine learning is key to ensure content is up-to-date, practical and engaging. This is a full-time role where you will constantly be challenged to learn and be curious about ML.As a Sr. MLU Applied Scientist on our team, you would have the following responsibilities:· Teach customers directly to understand their business problems, and help them with defining and implementing scalable ML/DL solutions to solve them· Develop open-source curriculum designed to provide a practical knowledge of ML. This includes lectures, videos, demos, and coding notebook assignments (find an article about our largest release here: https://www.amazon.science/latest-news/machine-learning-course-free-online-from-amazon-machine-learning-university)· Collaborate with scientists across Amazon to continuously understand and integrate advances in ML into the curriculum· Help drive high-level curriculum decisions to ensure alignment with students’ needs and the state-of-the-art domains of advancement in ML· Consult with customers on model development and deployment best practices by using computer science fundamentals· Engage in the interview process and otherwise develop, grow, and mentor junior scientistsThis team is comprised of Data Scientists, Applied Scientists and Instructional Designers to create first-in-class courses and learning assets in practical ML. The role may require travel up to 40% of the time (pending safety protocols and travel restrictions). We are currently recruiting for talented individuals for this role in the following cities: London, Cambridge, Tuebingen, Dublin, Amsterdam, Berlin, Paris, or Gdansk. Let’s bring ML to everyone and demystify and democratize technology together!Inclusive Team CultureHere at AWS, we embrace our differences. We are committed to furthering our culture of inclusion. We have ten employee-led affinity groups, reaching 40,000 employees in over 190 chapters globally. We have innovative benefit offerings, and host annual and ongoing learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences.Work/Life BalanceOur team puts a high value on work-life balance. It isn’t about how many hours you spend at home or at work; it’s about the flow you establish that brings energy to both parts of your life. We believe striking the right balance between your personal and professional life is critical to life-long happiness and fulfilment. We offer flexibility in working hours and encourage you to find your own balance between your work and personal lives.Mentorship & Career GrowthOur team is dedicated to supporting new members. We have a broad mix of experience levels and tenures, and we’re building an environment that celebrates knowledge sharing and mentorship. We Hire and Develop the best so you can expect support in advancing your career ambitions and projects which will help you grow and develop your skills.
DE, BE, Berlin
Machine Learning (ML) has been strategic to Amazon from the early years. We are pioneers in areas such as recommendation engines, product search, eCommerce fraud detection, and large-scale optimization of fulfillment center operations.Machine Learning University’s (MLU) mission is to teach people to apply ML to business and operational challenges. In service of this goal, we are growing our presence outside the US, and are looking to hire in EMEA region. We believe strongly that a practical knowledge of ML can be taught broadly, and is a key skill for many builders to learn. Come join Amazon’s MLU and help spread knowledge of ML!We have built a team of passionate science educators with the demonstrated ability to explain ML to an audience of technical professionals, enhance curriculum, and collaborate with scientists across the company. You will teach practitioners how to train, tune, and deploy ML models to solve challenges in customer segmentation, fraud prevention, capacity planning, predictive maintenance, pricing optimization, call center analtyics, and event detection among others. Practical experience with machine learning is key to ensure content is up-to-date, practical and engaging. This is a full-time role where you will constantly be challenged to learn and be curious about ML.As a MLU Applied Scientist on our team, you would have the following responsibilities:· Teach customers directly to understand their business problems, and help them with defining and implementing scalable ML/DL solutions to solve them· Develop open-source curriculum designed to provide a practical knowledge of ML. This includes lectures, videos, demos, and coding notebook assignments (find an article about our largest release here: https://www.amazon.science/latest-news/machine-learning-course-free-online-from-amazon-machine-learning-university)· Collaborate with scientists across Amazon to continuously understand and integrate advances in ML into the curriculum· Help drive high-level curriculum decisions to ensure alignment with students’ needs and the state-of-the-art domains of advancement in ML· Consult with customers on model development and deployment best practices by using computer science fundamentalsThis team is comprised of Data Scientists, Applied Scientists and Instructional Designers to create first-in-class courses and learning assets in practical ML. The role may require travel up to 40% of the time (pending safety protocols and travel restrictions). We are currently recruiting for talented individuals for this role in the following cities: London, Cambridge, Tuebingen, Dublin, Amsterdam, Berlin, Paris, or Gdansk. Let’s bring ML to everyone and demystify and democratize technology together!Inclusive Team CultureHere at AWS, we embrace our differences. We are committed to furthering our culture of inclusion. We have ten employee-led affinity groups, reaching 40,000 employees in over 190 chapters globally. We have innovative benefit offerings, and host annual and ongoing learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences.Work/Life BalanceOur team puts a high value on work-life balance. It isn’t about how many hours you spend at home or at work; it’s about the flow you establish that brings energy to both parts of your life. We believe striking the right balance between your personal and professional life is critical to life-long happiness and fulfilment. We offer flexibility in working hours and encourage you to find your own balance between your work and personal lives.Mentorship & Career GrowthOur team is dedicated to supporting new members. We have a broad mix of experience levels and tenures, and we’re building an environment that celebrates knowledge sharing and mentorship. We Hire and Develop the best so you can expect support in advancing your career ambitions and projects which will help you grow and develop your skills.
US, WA, Seattle
Job summaryThe AWS Cryptography Group is looking for an Applied Scientist with knowledge of cryptographic computing technologies such as privacy preserving machine learning, fully and partially homomorphic encryption, secure multiparty computation, private information retrieval, and related technologies. You will use this knowledge to conceptualize how this technology can be integrated into internal infrastructure and public AWS services, develop prototypes, and provide customers with world-class security. The ideal candidate will have a strong understanding of cryptography, the ability to prototype solutions, and a passion to realize these technologies in AWS products and services. We encourage research and publication of results that apply to our customers most complex initiatives.We are seeking a candidate who is innovative, looking for new ideas everywhere. They should think big, and have bold ideas for new ways to serve customers.About UsAWS has the most services and more features within those services, than any other cloud provider–from infrastructure technologies like compute, storage, and databases–to emerging technologies, such as machine learning and artificial intelligence, data lakes and analytics, and Internet of Things. AWS Platform is the glue that holds the AWS ecosystem together. Whether its Identity features such as access management and sign on, cryptography, console, builder & developer tools, and even projects like automating all of our contractual billing systems, AWS Platform is always innovating with the customer in mind. The AWS Platform team sustains over 750 million transactions per second.A Culture of InclusionHere at AWS, we embrace our differences. We are committed to furthering our culture of inclusion. We have ten employee-led affinity groups, reaching 40,000 employees in over 190 chapters globally. We have innovative benefit offerings, and we host annual and ongoing learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences. Amazon’s culture of inclusion is reinforced within our 14 Leadership Principles, which remind team members to seek diverse perspectives, learn and be curious, and earn trust.Work/Life BalanceWe put a high value on work-life balance. It isn’t about how many hours you spend at home or at work; it’s about the flow you establish that brings energy to both parts of your life. We believe striking the right balance between your personal and professional life is critical to life-long happiness and fulfillment. We offer flexibility in working hours and encourage you to find your own balance between your work and personal lives.Mentorship & Career GrowthOur team is dedicated to supporting new members. We have a broad mix of experience levels and tenures, and we’re building an environment that celebrates knowledge sharing and mentorship. We provide both the opportunity to be mentored by seasoned leaders and to mentor junior researchers. We care about your career growth and strive to give you challenging responsibilities that will help you develop into a better-rounded applied scientist and give you the opportunity to advance your career to the next level.Learn more about Amazon on our Day 1 Blog: https://blog.aboutamazon.com/
US, VA, Arlington
Job summaryThe Group:The Database Services group provides rapidly growing, industry acclaimed cloud services in areas of big data platforms, data warehouses, analytics, and operational databases. The group is at the forefront of innovation in these areas producing world-class cloud services, which while large profitable businesses, are also in their infancy. They represent a large fraction of the AWS business, and continue to accelerate.The Team:Lake Formation is our fully managed service to simplify building and securing data lakes. It features Blueprints to ingest data from commons sources, ML transforms to clean and de-duplicate data and a unified security model with fine-grained permissions (at the database, table, and column level) that are applicable across a wide range of AWS analytic and ML services (Redshift Spectrum, Glue, EMR Spark, QuickSight).The Lake Formation team is looking for an Applied Scientist with experience in building secure, scalable solutions that delight customers. You will apply your knowledge to propose solutions, create software prototypes, and productize prototypes into production systems using software development tools and methodologies. In addition, you will support and scale your solutions to meet the ever-growing demand of customer use. You have strong verbal and written communication skills, are self-driven and deliver high quality results in a fast-paced environment.Technical Responsibilities:· Interact with various teams to develop an understanding of their security and safety requirements.· Apply the acquired knowledge to build tools find problems, or show the absence of security/safety problems.· Implement these tools through the use of SAT, SMT, BDDs, and various concepts from programming languages, theorem proving, formal verification and constraint solving.· Perform analysis of the customer systems using tools developed in-house or externally provided· Create software prototypes to verify and validate the devised solutions methodologies; integrate the prototypes into production systems using standard software development tools and methodologies.Inclusive Team CultureHere at AWS, we embrace our differences. We are committed to furthering our culture of inclusion. We have ten employee-led affinity groups, reaching 40,000 employees in over 190 chapters globally. We have innovative benefit offerings, and we host annual and ongoing learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences. Amazon’s culture of inclusion is reinforced within our 14 Leadership Principles, which remind team members to seek diverse perspectives, learn and be curious, and earn trust.Work/Life BalanceOur team puts a high value on work-life balance. It isn’t about how many hours you spend at home or at work; it’s about the flow you establish that brings energy to both parts of your life. We believe striking the right balance between your personal and professional life is critical to life-long happiness and fulfillment. We offer flexibility in working hours and encourage you to find your own balance between your work and personal lives.Mentorship & Career GrowthOur team is dedicated to supporting new members. We have a broad mix of experience levels and tenures, and we’re building an environment that celebrates knowledge sharing and mentorship. Our senior members enjoy one-on-one mentoring and thorough, but kind, code reviews. We care about your career growth and strive to assign projects based on what will help each team member develop into a better-rounded engineer and enable them to take on more complex tasks in the future.