AfroTech  Dela Agbemabiese Justin Barry Nashlie Sephus 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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The Organizational Research and Measurement team conducts research supporting all Amazon corporate employees. Our goal is to build talent systems to enable employees to thrive at Amazon. We focus on the entire employee life-cycle to improve both business and employee outcomes. This entails doing longitudinal survey research, organizational network analysis, experimental and quasi-experimental studies for causal inference, building services that plug-in to other tools, and providing general consultation to stakeholders. We aim to improve the outcomes of our business and employees by doing cutting edge social science research.The Role:As a Data Scientist at Amazon, your main focus will be on developing predictive models, simulation, visualization, and support structures for data analysis.
US, WA, Seattle
The Organizational Research and Measurement team conducts research supporting all Amazon corporate employees. Our goal is to build talent systems to enable employees to thrive at Amazon. We focus on the entire employee life-cycle to improve both business and employee outcomes. This entails doing longitudinal survey research, organizational network analysis, experimental and quasi-experimental studies for causal inference, building services that plug-in to other tools, and providing general consultation to stakeholders. We aim to improve the outcomes of our business and employees by doing cutting edge social science research.The Role:As a Research Scientist at Amazon, you will apply scientific principles, subject matter expertise, and business acumen to deliver results at scale by conducting employee life-cycle research.Key Responsibilities:· Supporting global-scale research initiatives across multiple business segments and implementing a wide range of scientific methodologies to solve stakeholder problems.· Collaborating with a cross-functional team that has expertise in the social sciences (e.g., econometrics, psychometrics, judgement and decision making models), machine learning, data science, data engineering, and business intelligence· Querying from multiple data sources, data cleaning and exploration, and advanced statistical analysis.· Writing high-quality, evidence-based documents that help provide insights to business leaders and gain buy-in.· Convert evidence-based insights into usable products, services, or tools for stakeholders.· Serving as a subject matter expert on a wide variety of topics related to research design, measurement, and analysis.· Sharing knowledge, advocating for innovative solutions, and supporting team members.
US, WA, Seattle
The AWS Central Economics team is looking for a PhD economist. The ideal candidate will have experience with time-series forecasting.You will learn about cloud products, including compute, storage, and databases. You will work on analytic projects requested by senior leadership. You will get the opportunity to learn new techniques. You will be a part of a team with many experienced economists.Amazon is an Equal Opportunity-Affirmative Action Employer – Minority / Female / Disability / Veteran / Gender Identity / Sexual Orientation
US, WA, Seattle
The Organizational Research and Measurement (ORM) Team within World Wide Consumer guides the talent strategy for Amazon’s largest workforce comprised of over one million Amazon global employees across order fulfillment, transportation, corporate, consumer, and customer service organizations. We are an interdisciplinary team that combines the talents of science and engineering to develop and deliver data products and solutions across the employee lifecycle including onboarding; high-potential identification; talent development; engagement; movement; retention; and attrition.We are looking for an applied scientist who is able to engineer end-to-end solutions for complex science and business problems around the future of talent evaluation, development, and management at Amazon. You will work closely with I/O psychologists, economists, engineers, and business partners to estimate and validate models on large scale data, and turn the results of these analyses into products, policies, programs, and actions that have a major impact on Amazon’s business. We are looking for creative thinkers who can combine strong data science, software engineering, UX and product development skillsets with a desire to innovate, and who know how to execute and deliver on big ideas.Key Responsibilities· Develop of start-to-finish data product solutions from requirements gathering and ideation, through interface design and implementation.· Design data infrastructure and pipelines for machine learning and analytics products.· Obtain, merge, analyze, and report data using SQL, statistics software, and data visualization tools.· Apply various statistical and machine learning techniques to analyze large and complex data sets.· Communicate applied machine learning and statistic concepts to project sponsors, business leaders, and development teams across Amazon.· Understand business customer needs, iterate on feedback, and drive adoption
US, WA, Seattle
The Organizational Research and Measurement (ORM) Team within World Wide Consumer guides the talent strategy for Amazon’s largest workforce comprised of over one million Amazon global employees across order fulfillment, transportation, corporate, consumer, and customer service organizations. We are an interdisciplinary team that combines the talents of science and engineering to develop and deliver data products and solutions across the employee lifecycle including onboarding; high-potential identification; talent development; engagement; movement; retention; and attrition.We are looking for an applied scientist who is able to engineer end-to-end solutions for complex science and business problems around the future of talent evaluation, development, and management at Amazon. You will work closely with I/O psychologists, economists, engineers, and business partners to estimate and validate models on large scale data, and turn the results of these analyses into products, policies, programs, and actions that have a major impact on Amazon’s business. We are looking for creative thinkers who can combine strong data science, software engineering, UX and product development skillsets with a desire to innovate, and who know how to execute and deliver on big ideas.Key Responsibilities· Develop of start-to-finish data product solutions from requirements gathering and ideation, through interface design and implementation.· Design data infrastructure and pipelines for machine learning and analytics products.· Obtain, merge, analyze, and report data using SQL, statistics software, and data visualization tools.· Apply various statistical and machine learning techniques to analyze large and complex data sets.· Communicate applied machine learning and statistic concepts to project sponsors, business leaders, and development teams across Amazon.· Understand business customer needs, iterate on feedback, and drive adoption
PL, Gdansk
Come and join the Database Migration Accelerator team that helps our customers migrate to the cloud. We are on a mission to transform legacy enterprise workloads into modern AWS native application architectures. We achieve this by utilizing cutting edge tools, sophisticated engineering systems and database expertise. We provide fixed price and high speed migrations to the cloud. Database Migration Accelerator is combining various AWS cloud platform services into one product which would serve our customers.We are a team of professionals that are forward-looking and using latest technology offerings (AWS cloud services, Machine Learning, Mathematical Optimization, Relational and NoSQL databases) to build new capability to operationalize and automate migration methodologies. Databases Services at AWS cover a range of data platforms including: Amazon Aurora, DynamoDB, Redshift, Athena, as well as AWS Database Migration Service, Data Pipeline, Glue and more. As each service grows, so does adoption by customers world-wide.We have an opportunity for a Senior Applied Scientist who is passionate about combining machine learning with developing new offerings for the cloud and is enthusiastic about applying bold new ideas to real-world problems.Joining the AWS Database Services team as a Senior Applied Scientist gives you the opportunity to:· Work for a company that’s at the forefront of the cloud computing space.· Be a part of something unique what no other previously developed and was successful.· Design machine learning solutions to intelligently move enterprises to the cloud.· Truly own the solution from concept design through development to production.· Join the team whose activities are regularly called out publicly by AWS CEO Andy JassyWork/Life BalanceOur team places value on work-life balance. Our team is global, based in the US and Poland. Our Poland teams typically start later in the day to have a couple of hours of overlap with US teams.Mentorship & Career GrowthOur team is dedicated to supporting new team members in an environment that celebrates knowledge sharing and mentorship. Our senior engineers mentor more junior engineers through one-on-one mentoring and collaborative code reviews. Projects and tasks are assigned in a way that leverages your strengths and helps you further develop your skillset.Inclusive Team CultureWe get to build a really cool service and the main contributing factor to our success is the inclusive and welcoming culture that we embody every day.We welcome teammates who are enthusiastic, empathetic, curious, motivated, reliable, and able to collaborate with a diverse team of peers.As a Senior Applied Scientist, your responsibilities will include:· Building new cloud based Machine Learning solutions and algorithms to accelerate migrations to the cloud· Participating in hands-on machine learning experimentation and delivering the results in the form of new products· Creating technical strategies and delivering with limited guidance· Solving difficult and complex software problems. Your solutions should be extensible· Cross-collaborating with a number of different teams with overlapping work, including solutions architects, developers, product managers, senior leaders, and many more· Mentoring more junior members of the team or collaboration partners
PL, Gdansk
Come and join the Database Migration Accelerator team that helps our customers migrate to the cloud. We are on a mission to transform legacy enterprise workloads into modern AWS native application architectures. We achieve this by utilizing cutting edge tools, sophisticated engineering systems and database expertise. We provide fixed price and high speed migrations to the cloud. Database Migration Accelerator is combining various AWS cloud platform services into one product which would serve our customers.We are a team of professionals that are forward-looking and using latest technology offerings (AWS cloud services, Machine Learning, Mathematical Optimization, Relational and NoSQL databases) to build new capability to operationalize and automate migration methodologies. Databases Services at AWS cover a range of data platforms including Amazon Aurora, DynamoDB, Redshift, Athena, as well as AWS Database Migration Service, Data Pipeline, Glue and more. As each service grows, so does adoption by customers world-wide.We have an opportunity for a Senior Applied Scientist who is passionate about mathematical optimization with developing new offering for the cloud and is enthusiastic about applying bold new ideas to real-world problems.Joining the AWS Database Services team as a Senior Applied Scientist gives you the opportunity to:· Work for a company that’s at the forefront of the cloud computing space· Be a part of something unique what no other previously developed and was successful.· Design mathematical optimization algorithms to intelligently move enterprises to the cloud.· Truly own solution from concept design through development to production· Join the team whose activities are regularly called out publicly by AWS CEO Andy JassyWork/Life BalanceOur team places value on work-life balance. Our team is global, based in the US and Poland. Our Poland teams typically start later in the day to have a couple of hours of overlap with US teams.Mentorship & Career GrowthOur team is dedicated to supporting new team members in an environment that celebrates knowledge sharing and mentorship. Our senior engineers mentor more junior engineers through one-on-one mentoring and collaborative code reviews. Projects and tasks are assigned in a way that leverages your strengths and helps you further develop your skillset.Inclusive Team CultureWe get to build a really cool service and the main contributing factor to our success is the inclusive and welcoming culture that we embody every day.We welcome teammates who are enthusiastic, empathetic, curious, motivated, reliable, and able to collaborate with a diverse team of peers.As a Senior Applied Scientist, your responsibilities will include:· Build new cloud based mathematical solutions and algorithms to accelerate migrations to the cloud· Participate in algorithms experimentation and deliver the results in the form of new products· Develop scalable optimization algorithms for moving customer workloads to cloud environments. Create technical strategies and deliver with limited guidance· Creating technical strategies and delivering with limited guidance· Solving difficult and complex software problems. Your solutions should be extensible· Cross-collaborating with a number of different teams with overlapping work, including solutions architects, developers, product managers, senior leaders, and many more· Mentoring more junior members of the team or collaboration partners
US, NY, New York
MULTIPLE POSITIONS AVAILABLEEntity: Amazon.com Services LLCPosition: Data Scientist IILocation: New York, NYPosition Responsibilities:Design and implement scalable and reliable approaches to support or automate decision making throughout the business. Apply a range of data science techniques and tools combined with subject matter expertise to solve difficult business problems and cases in which the solution approach is unclear. Acquire data by building the necessary SQL / ETL queries. Import processes through various company specific interfaces for accessing Oracle, RedShift, and Spark storage systems. Build relationships with stakeholders and counterparts. Analyze data for trends and input validity by inspecting univariate distributions, exploring bivariate relationships, constructing appropriate transformations, and tracking down the source and meaning of anomalies. Build models using statistical modeling, mathematical modeling, econometric modeling, network modeling, social network modeling, natural language processing, machine learning algorithms, genetic algorithms, and neural networks. Validate models against alternative approaches, expected and observed outcome, and other business defined key performance indicators. Implement models that comply with evaluations of the computational demands, accuracy, and reliability of the relevant ETL processes at various stages of production.Amazon.com is an Equal Opportunity-Affirmative Action Employer – Minority / Female / Disability / Veteran / Gender Identity / Sexual Orientation #0000
US, WA, Seattle
Amazon Web Services is looking for world class scientists to join the Security Analytics and AI Research group within AWS Security Services. This team is entrusted with researching and developing core data mining and machine learning algorithms for various AWS security services like GuardDuty (https://aws.amazon.com/guardduty/) and Macie (https://aws.amazon.com/macie/). On this team, you will invent and implement innovative solutions for never-before-solved problems. If you have a passion for security and experience with large scale machine learning problems, this will be an exciting opportunity.The AWS Security Services team builds technologies that help customers strengthen their security posture and better meet security requirements in the AWS Cloud. The team interacts with security researchers to codify our own learnings and best practices and make them available for customers. We are building massively scalable and globally distributed security systems to power next generation services.Key Responsibilities:· Rapidly design, prototype and test many possible hypotheses in a high-ambiguity environment, making use of both quantitative and business judgment· Collaborate with software engineering teams to integrate successful experiments into large scale, highly complex production services· Report results in a scientifically rigorous way· Interact with security engineers and related domain experts to dive deep into the types of challenges that we need innovative solutions forHere 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.
AT, Graz
Location: Graz, AustriaDuration: 3-6 monthsAbout us:We are working on the future. If you are seeking an innovative, fast-paced environment where you can apply state-of-the-art technologies to solve extreme-scale real world challenges and provide visible benefit to end-users, this is your opportunity: Come work on the Amazon Prime Air team!We are looking for an outstanding computer vision / machine learning applied scientist who combines superb technical, research and analytical capabilities with a demonstrated ability to get the right things done quickly and effectively. This person must be comfortable working with a team of top-notch applied scientists. We are looking for someone who innovates and loves solving hard problems. You will work hard, have fun, and of course, make history!Export Control License: This position may require a deemed export control license for compliance with applicable laws and regulations. Placement is contingent on Amazon’s ability to apply for and obtain an export control license on your behalf.About those internship roles:Are you inspired by innovation? Is problem solving through teamwork in your DNA? Do you like the idea of seeing how your work impacts the bigger picture? If your answer is yes then you’ll fit right in here. We are a smart team of doers that work passionately to apply cutting edge advances in autonomous drone delivery and software to solve real-world challenges that will transform our customers’ experiences in ways we can’t even image yet. We invent new improvements every day. We are Amazon Prime Air and we will give you the tools and support you need to invent with us in ways that are rewarding, fulfilling and fun.Prime Air at Amazon is seeking a talented and motivated student to join the Prime Air team for an Internship assignment. The candidate will have the opportunity to work with senior engineering staff on existing and new modules and systems. The ideal candidate has solid coding skills, enjoys problem solving and has at least one of the following: strong computer vision skills, strong machine-learning skills, or, strong computer graphics skills.Applicants should have at a minimum one quarter/semester remaining after their internship concludes.As an Applied Scientist intern, you will be responsible for data-driven improvements to our product. Regardless of the team you join, your work will directly impact our customers. You will:· Collaborate with colleagues from science, engineering and business backgrounds.· Present proposals and results in a clear manner backed by data and coupled with actionable conclusions.· Push the state-of-the-art in computer vision, machine learning or computer graphics for large-scale real world problems.· Summarize and present your contributions in a white paper or peer reviewed scientific publication.
US, WA, Seattle
The Amazon Economics Team is hiring Interns in Economics. We are looking for detail-oriented, organized, and responsible individuals who are eager to learn how to work with large and complicated data sets. Some knowledge of econometrics, as well as basic familiarity with Stata or R is necessary, and experience with SQL, UNIX, and Sawtooth would be a plus.These are full-time positions at 40 hours per week, with compensation being awarded on an hourly basis. You will learn how to build data sets and perform applied econometric analysis at Internet speed collaborating with economists, data scientists and MBAʼs. These skills will translate well into writing applied chapters in your dissertation and provide you with work experience that may help you with placement.Roughly 50% of research assistants from previous cohorts have converted to full time data science or economics employment at Amazon. If you are interested, send your CV, transcripts, and a cover letter to our mailing list at econ-internship@amazon.com.Amazon is an Equal Opportunity-Affirmative Action Employer – Minority / Female / Disability / Veteran / Gender Identity / Sexual Orientation