A grid of 12 women scientists who were asked what three steps we can take as a society to forge a more gender-equal science community
As International Women's Day approached, we asked women scientists from research areas across the company what three steps we can take as a society to forge a more gender-equal science community.
Credit: Glynis Condon

How to forge a more gender-equal science community

International Women's Day is March 8 with the theme: #ChooseToChallenge.

International Women’s Day (IWD) is March 8, 2021. The day celebrates the social, economic, cultural and political achievements of women, and also denotes a call to action to accelerate gender parity. This year’s theme: #ChooseToChallenge.

“From challenge comes change, so let’s all choose to challenge,” says the IWD website.

As IWD approached, Amazon Science asked women scientists from research areas across the company what three steps we can take as a society to forge a more gender-equal science community. Below are their responses.

Bouchra Bouqata

Bouchra is a senior applied scientist within Amazon Robotics. She earned her PhD in machine learning and artificial intelligence from Rensselaer Polytechnic Institute.

  • Provide a clear pipeline for advancing and promoting women’s careers in science. Companies and institutions should adopt gender-balanced peer review promotion processes and committees.  They should also provide special funds and grants to help women scientists further their research and work.
  • Conferences and publishing venues should adopt gender-conscious peer-review committee, and speaker- selection committee recruitment processes.
  • Companies and institutions should commit to educating everyone, not just leadership, to combat the issues facing women in science. They should provide gender awareness training as a standard component of any training they provide to their employees and members. They should provide seminars and convene roundtable discussions on gender issues in science to facilitate communication and identification of solutions.

Nilay Noyan Bulbul

Nilay is a principal scientist within the company’s Supply Chain Optimization Technologies organization.  She earned her PhD in operations research from Rutgers University.

  • Call the gender disparity out: Identify where women scientists are marginalized, and call out the disparity to ensure fair representation at the leadership of scientific research and decision-making, as well as “invite-only” prestigious roles, such as keynote speaking engagements, prize juries, and journal editorial board memberships.
  • Invest in the future: Create more initiatives and opportunities for the next generation of women scientists via mentoring and targeted prize and research fund calls.
  • Keep everyone accountable: Make sure every entity working towards gender equality in science community has a tangible way to measure the “change” and keep track of the progress, and make the process transparent.”

Cindy Cui

Cindy is a senior economist within the Alexa Shopping organization. She earned her PhD in economics from the University of Texas at Austin.  

Role models, aspirations, and supportive community are most important factors to me. Growing up, my grandma taught me reading and math. I still remember the days when we would go through math problems and I felt happy and proud when I solved them correctly.

My grandma is also one of the few female teachers in her generation and always emphasizes the importance of education and hard work. In school, many smart female classmates encouraged and challenged me throughout.

It takes all of us to improve gender equality in science, doing our best and helping others along the way.

Donna Dodson

Donna is a senior principal technologist within the AWS Security organization. She earned her master’s degree in computer science from Hood College.

  • Build a culture that values deep thinkers who balance speaking and listening to others. Often the subculture’s voices — including women’s — are not heard.
  • Create compensation, incentives, benefits, resources, recognition and a flexible workplace that balance needs at different stages in life. Early- and mid-career scientists with families require flexibility for a work-life balance.
  • Recognize and promote diverse voices throughout K-12 science programs to empower girls to grow their confidence in science knowledge, skills and abilities

Maryam Fazel-Zarandi

Maryam is a senior machine learning scientist within the Alexa AI organization. She earned her PhD in computer science at the University of Toronto.

Maryam Fazel-zarandi
Maryam Fazel-Zarandi
Credit: Pierce Harman Photography

I have been able to pursue my dream of becoming a scientist and have had access to role models and mentors throughout my education and career. The number of women scientists like me has increased over the past decades, however, we are still far from a gender equal science community.

While we should continue to reduce the large gap that still exists in terms of numbers, in my opinion, we should put more focus on mechanisms to retain women scientists. Lack of support for women in difficulty, feelings of isolation at work, and unmet expectations are among the top reasons why women leave their careers in science. The COVID-19 pandemic has further contributed to these difficulties as more women are taking additional caregiver roles at home, which in turn impacts their continued employment and career advancement.

To forge a more gender-equal global science community, we need to promote women’s integration in the research environment and workplace by learning about women’s experiences and providing direct support for women in difficulty. Our institutions and organizations should also implement and monitor measures to ensure womens’ career development in a post-pandemic world.

Rashmi Gangadharaiah

Rashmi is a senior research scientist within the AWS organization. She earned her PhD in information technology, artificial intelligence, and machine learning from Carnegie Mellon University.

As a woman and a mother of two girls, I’m glad that gender equality has been receiving more attention. Just talking about gender equality doesn’t mean that we’ve created a gender-equal community. Here are three steps that we can take to create a gender-equal global science community.

  1. Create opportunities that encourage more women to tackle challenging projects.
  2. Recognize women who have an impact on projects and give credit where it’s due.
  3. We as women should not be afraid to take on challenging projects, grab opportunities that come our way and have a community/support system when the deck is stacked against us.

Antia Lamas-Linares

Antia is a principal research scientist within the AWS Center for Quantum Computing. She earned her PhD in physics from the University of Oxford.

Helping diversify science is often not about actions within science, but immediately around science; removing the “death by a thousand cuts” problems.

The most impactful action we can take to improve science careers for women is to prioritize affordable childcare in research campuses (both university and industrial). This also has the very nice feature of benefiting the whole community of researchers, but it would have a disproportionate effect on women, while avoiding the insidious problems of preferential treatment.

If we can make space in campuses for exercise and culture, we can make space for daycares. A second thing we could do is prominently feature female scientists without remarking on their gender, they should not be an anomaly that needs to be highlighted and this narrative can be gently pushed from within organizations. Thirdly, and this is more of a personal action, actively avoid discouraging girls for pursuing geeky interests. Boys get rewarded with questions and attention for this behavior. Girls get the opposite signals.

Bilan Liu

Bilan is an applied robotics scientist within the company’s Lab126 organization. She earned her PhD in electrical and computer engineering at the University of Rochester.

  • The key aspect for a gender equal world is an environment where women share the same opportunities as men, such as quality education.
  • A gender equal world not only calls for the equality of women, but also quality among women. It is beneficial to share the recognition of successful women, as well as to have supportive peers and mentors for young women.
  • We should advocate to elevate women’s voices, both in the workplace and the media. Increasing the representation of women in a workplace not only creates a better workplace, it also changes perceptions about the value that women bring to the table.

Catherine Benoit Norris

Catherine is a science researcher within the company’s Sustainability organization.  She earned her PhD in business administration from the Université du Québec à Montréal.

  • Acknowledge and support workers, students, professionals, and scientists as parents. Until we fully recognize the needs of families, and have a work culture that allows setting limits, women will continue to be held back.
  • Make sure that everyone speaks and are listened to in meetings. Making sure that everybody is being heard and are being paid attention to when they speak is fundamental for a gender-equal global science community.
  • Support, encourage, value, and recognize women academic achievements. Publicly valuing, rewarding, and celebrating competence and achievements in women is a stepping stone towards gender equality in science and beyond.

Tara Taghavi

Tara is a senior applied scientist within the Alexa AI organization. She earned her PhD in computer science from the University of California, Los Angeles.

A first step in promoting gender equality is to involve more women in hiring processes, particularly hiring loops for science roles.

A second step is to facilitate a more favorable work environment for mothers by providing alternate hours, a reduced time schedule, and similar measures so women can grow their careers as they grow their families.

A third step is to empower women to take management roles. Many statistics have been shared regarding the disproportionate number of women who are promoted in comparison to their male counterparts. We should address it by encouraging women to pursue these roles, and then supporting them as they take on the responsibilities of these higher-level roles.

Nedelina Teneva

Nedelina is an applied scientist (search) within the Alexa organization. She earned her PhD in computer science from the University of Chicago.

Engaging in cross-disciplinary collaborations forces us to be curious, empowers us to say “I don’t know” and ask others “What do you think?”. 

This helps us better understand others’ lived experiences. In both professional and personal collaborations, we need to apply more rigorously the scientific method, which minimizes the influence of prejudice, by recognizing our biases or pre-existing beliefs and designing appropriate management strategies.

Finally, we need to continue to solidify these processes into platforms and organizations that nurture diverse opinions. Lessons learned from the existing diversity/inclusion efforts within the science community should be utilized in the broader society. 

Nikhita Vedula

Nikhita is an applied scientist with the Alexa Shopping organization. She earned her PhD in computer science and engineering from Ohio State University.

Education, encouragement, and awareness are key to fostering the growth of a more gender-equal science community.  Throughout my studies — straight through the completion of my PhD — I have seen at best an 80-20 ratio of men to women in classrooms, and academic or industrial positions. This needs to change, and this change needs to begin within our homes.    

Women require support from both men and other women alike, right from their childhood. We need to inspire and motivate women to nurture their dreams, and pursue their unique passions, instead of telling them things like “This field is for men, not for you”.

View from space of a connected network around planet Earth representing the Internet of Things.
Sign up for our newsletter

Research areas

View from space of a connected network around planet Earth representing the Internet of Things.
Get more from Amazon Science
Sign up for our monthly newsletter

Work with us

See more jobs
US, CA, Milpitas
We are a passionate team of doers that apply cutting-edge advances in technology to solve real-world problems and transform our customers’ experiences in ways we can’t even imagine yet. As an Applied Scientist, you will be working with a unique and gifted team developing exciting products for customers and collaborating with cross-functional teams.Responsibilities· Collaborate across functions to , develop and implement algorithms to solve high-impact problems· Evaluate statistical modeling and Machine Learning approaches using historical data· Define requirements and measurement criteria for scientific and machine learning models.· Translate model prototypes into secure, stable, testable, and maintainable production services.· Develop automated approaches towards monitoring model performance and evaluating impact.· Encourage and support knowledge-sharing within team and external groups· Responsible for influencing technical decisions in areas of /modelling that you identify as critical future offerings· Deliver algorithm and ML projects from beginning to end, including understanding the customer needs, aggregating data, exploring data, building & validating predictive models, and deploying completed models.Amazon is looking for an Applied Scientist to join an exciting new project team working to build a completely new, best in class . Our team is fast paced, highly collaborative and is organized like a startup.Here at Amazon, 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.Our 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 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.Our 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.Our main office is Milpitas Ca but other US-based Amazon centers are ok.
US, VA, Arlington
Are you seeking an environment where you can drive innovation? Do you want to apply machine learning techniques and advanced statistical modeling to solve real world problems to help Amazon reach and delight millions of customers around the world? Do you want to play a crucial role in the future of Amazon?Every time an Amazon customer makes an order they leverage the most advanced and sophisticated supply chain the world has ever seen, Amazon, and its global network comprising of cutting edge software, fulfillment centers, sort centers, delivery stations, airports, customer service centers, physical stores, robots, airplanes, trucks, vans, trucks, world class employees, trusted partners, and more. Conducting a symphony of this scale comes with significant costs.Here in WW Consumer Finance, our data scientists raise the bar on our ability to fulfill promises to customers at greater convenience, speed, and value through:· Developing visual solutions which help Amazonians search, find, compare, and buy goods / services critical to Amazon's operations· Developing production-ready machine learning solutions to drive savings across Amazon's corporate procurement catalog· Working with technical and non-technical customers across every step of data science project life cycle.· Collaborating with our dedicated product, data engineering, and software development teams to create production implementations for large-scale data analysis.· Developing an understanding of key business metrics / KPIs and providing clear, compelling analysis that shapes the direction of our business.· Presenting research results to our internal research community.· Leading training and informational sessions on our science and capabilities.Your contributions will be seen and recognized broadly within Amazon, potentially contributing to the Amazon research corpus and patent portfolio.
US, VA, Arlington
Are you seeking an environment where you can drive innovation? Do you want to apply machine learning techniques and advanced statistical modeling to solve real world problems to help Amazon reach and delight millions of customers around the world? Do you want to play a crucial role in the future of Amazon?Every time an Amazon customer makes an order they leverage the most advanced and sophisticated supply chain the world has ever seen, Amazon, and its global network comprising of cutting edge software, fulfillment centers, sort centers, delivery stations, airports, customer service centers, physical stores, robots, airplanes, trucks, vans, trucks, world class employees, trusted partners, and more. Conducting a symphony of this scale comes with significant costs.Here in WW Consumer Finance, our quantitative researchers raise the bar on our ability to fulfill promises to customers at greater convenience, speed, and value through:· Developing models to support the identification of investment opportunities consistent with Amazon strategic priorities· Developing models identifying synergy opportunities and risks in potential transactions· Serving as a subject matter expert on investment lead pipeline and valuation methodologies· Establish the ongoing processes, skill sets, and strategy that will enable Amazon to continue to build out our financial engineering competency, in the face of extremely fast growth and a rapidly changing industry· Working with technical and non-technical customers across every step of data science project life cycle.· Collaborating with our dedicated product, data engineering, and software development teams to create production implementations for large-scale data analysis.· Developing an understanding of key business metrics / KPIs and providing clear, compelling analysis that shapes the direction of our business.· Presenting research results to our internal research community.· Leading training and informational sessions on our science and capabilities.Your contributions will be seen and recognized broadly within Amazon, potentially contributing to the Amazon research corpus and patent portfolio.
US, VA, Arlington
Are you seeking an environment where you can drive innovation? Do you want to apply machine learning techniques and advanced statistical modeling to solve real world problems to help Amazon reach and delight millions of customers around the world? Do you want to play a crucial role in the future of Amazon?Every time an Amazon customer makes an order they leverage the most advanced and sophisticated supply chain the world has ever seen, Amazon, and its global network comprising of cutting edge software, fulfillment centers, sort centers, delivery stations, airports, customer service centers, physical stores, robots, airplanes, trucks, vans, trucks, world class employees, trusted partners, and more. Conducting a symphony of this scale comes with significant costs.Here in WW Consumer Finance, our applied scientists raise the bar on our ability to fulfill promises to customers at greater convenience, speed, and value through:· Developing production ready solutions which help Amazonians search, find, compare, and buy goods / services critical to Amazon's operations· Developing production-ready machine learning solutions to improve Amazon's corporate procurement catalog· Working with technical and non-technical customers across every step of data science project life cycle.· Collaborating with our dedicated product, data engineering, and software development teams to create production implementations for large-scale data analysis.· Developing an understanding of key business metrics / KPIs and providing clear, compelling analysis that shapes the direction of our business.· Presenting research results to our internal research community.· Leading training and informational sessions on our science and capabilities.Your contributions will be seen and recognized broadly within Amazon, potentially contributing to the Amazon research corpus and patent portfolio.
US, VA, Arlington
Are you seeking an environment where you can drive innovation? Do you want to apply machine learning techniques and advanced statistical modeling to solve real world problems to help Amazon reach and delight millions of customers around the world? Do you want to play a crucial role in the future of Amazon?Every time an Amazon customer makes an order they leverage the most advanced and sophisticated supply chain the world has ever seen, Amazon, and its global network comprising of cutting edge software, fulfillment centers, sort centers, delivery stations, airports, customer service centers, physical stores, robots, airplanes, trucks, vans, trucks, world class employees, trusted partners, and more. Conducting a symphony of this scale comes with significant costs.Here in WW Consumer Finance our applied scientists raise the bar on our ability to fulfill promises to customers at greater convenience, speed, and value through:· Developing production ready solutions which help Amazonians search, find, compare, and buy goods / services critical to Amazon's operations· Developing production-ready machine learning solutions to improve Amazon's corporate procurement catalog· Working with technical and non-technical customers across every step of data science project life cycle.· Collaborating with our dedicated product, data engineering, and software development teams to create production implementations for large-scale data analysis.· Developing an understanding of key business metrics / KPIs and providing clear, compelling analysis that shapes the direction of our business.· Presenting research results to our internal research community.· Leading training and informational sessions on our science and capabilities.Your contributions will be seen and recognized broadly within Amazon, potentially contributing to the Amazon research corpus and patent portfolio.
US, WA, Seattle
We are constantly making Alexa the best voice assistant in the world. Amazon’s Alexa cloud service and Echo devices are used every day, by people you know, in and about their homes. The Alexa Monetization team is hiring talented and experienced Sr. Applied Scientists to help building the next generation products for Alexa across multiple channels and domains. We are seeking an experienced, entrepreneurial, big thinker for a confidential new initiative within Alexa. You will be joining a team doing innovative work, making a direct impact to customers, showing measurable success, and building with the latest natural language processing systems. If you are holding out for an opportunity to:Make a huge impact as an individual· Be part of a team of smart and passionate professionals who will challenge you to grow every day· Solve difficult challenges using your expertise in coding elegant and practical solutions· Create applications at a massive scale used by millions of people· Work with machine learning systems to deliver real experiences, not just researchAnd you are experienced with…· Drive applied science (machine learning) projects end-to-end ~ from ideation, analysis, prototyping, development, metrics, and monitoring· Conduct deep analyses on massive user and contextual data sets· Propose viable modeling ideas to advance optimization or efficiency, with supporting argument, data, or, preferably, preliminary results· Design, develop, and maintain scalable, Machine Learning models with automated training, validation, monitoring and reporting· Stay familiar with the field and apply state-of-the-art Machine Learning techniques to NLP and related optimization problems· Produce peer-reviewed scientific paper in top journals and conferencesAnd you constantly look for opportunities to…· Innovate, simplify, reduce waste, and increase efficiencies· Use data to make decisions and validate assumptions· Automate processes otherwise performed by humans· Learn from others and help grow those around you...then we would love to chat!In 2021, we have the opportunity to build new products and features from the ground up and we are looking for strong, bias for action engineering leaders who are not afraid of taking bold bets and trying new things to improve customer experience for Alexa.As part of a new and growing team, you will be iterating on new features and products to help drive innovation and expansion. You will work on cross-functional and cross-domain opportunities; tackle challenging projects aim to accelerate experimentations in Alexa; and build out operating mechanisms and technology to enable novel customer experiences. You will be instrumental in setting the team culture, quality bar, engineering best practices, and norms. Mentoring and growing the team around you will be one of the primary ways you measure your own success. You will have the opportunity to contribute and develop deep expertise in the areas of distributed systems, machine learning, conversational technologies, user interfaces (including voice and natural user interfaces), data storage and data pipelines.This role is exciting for scientists who love to apply startup mindset to their day-to-day, enjoy working cross-functionally to master both business and technology knowledge, and are passionate about building engineering best practices. If you are looking for opportunity to learn, grow and lead, this is the position for you.
IN, KA, Bengaluru
Do you want to join an innovative team of scientists who use machine learning and statistical techniques to create state-of-the-art solutions for providing better value to Amazon’s customers? Do you want to build and deploy advanced algorithmic systems that help optimize millions of transactions every day? Are you excited by the prospect of analyzing and modeling terabytes of data to solve real world problems? Do you like to own end-to-end business problems/metrics and directly impact the profitability of the company? Do you like to innovate and simplify? If yes, then you may be a great fit to join the Machine Learning and Data Sciences team for India Consumer Businesses.If you have an entrepreneurial spirit, know how to deliver, love to work with data, are deeply technical, highly innovative and long for the opportunity to build solutions to challenging problems that directly impact the company's bottom-line, we want to talk to you.Major responsibilities· · Use machine learning and analytical techniques to create scalable solutions for business problems· · Analyze and extract relevant information from large amounts of Amazon’s historical business data to help automate and optimize key processes· · Design, development, evaluate and deploy innovative and highly scalable models for predictive learning· · Research and implement novel machine learning and statistical approaches· · Work closely with software engineering teams to drive real-time model implementations and new feature creations· · Work closely with business owners and operations staff to optimize various business operations· · Establish scalable, efficient, automated processes for large scale data analyses, model development, model validation and model implementation· · Mentor other scientists and engineers in the use of ML techniques
US, CA, San Diego
.A day in the life.About the hiring group.Job responsibilitiesEconomistThe North American Consumer Economics team uses Economics, Statistics, and Machine Learning to understand and design the complex economy of Amazon’s network of buyers and sellers. We are an interdisciplinary team, committed to use of cutting edge technology and leveraging the strengths of engineers and scientists to build solutions for some of the toughest business problems at Amazon.We are looking for an outstanding Economist who is able to provide structure around complex business problems, work with machine learning scientists to estimate and validate their models on large scale data, and who can help business and tech partners turn the results of their analysis into policies, programs, and actions that have a major impact on Amazon’s business. We are looking for creative thinkers who can combine a strong economic toolbox with a desire to learn from others, and who know how to execute and deliver on big ideas.In this role, we expect you be able to own the development of economic models and to manage, in close collaboration with scientists and engineers, the data analysis, modeling, and experimentation that is necessary for estimating and validating your model. You will need to work with our business partners to communicate the properties of your analysis/modeling and be able to work to incorporate their feedback and requests into your project. Experience in applied economic analysis is essential, and you should be familiar with modern tools for data science and business analysis.We are particularly interested in candidates with research background in applied microeconomics, empirical IO, Marketing, Finance, applied econometrics, and market design. However, we want to talk with any experienced economist with an interest in working on an interest in working on innovative, strategic problems with significant business impact.Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us.
CA, BC, Vancouver
Are you passionate about driving business & customer impact through thoughtful analysis and data-driven insights? Are you a deeply technical individual who enjoys working with customers to transform how a business operates? Are you a builder that excels with ambiguity? Are you inspired by invention? Is problem solving through teamwork and working in a startup environment in your DNA? Do you like the idea of seeing how your work impacts the bigger picture?Answer yes to any of these and you’ll fit right in here.We are looking for Data Scientist professionals to drive our analytical revolution in the Talent Acquisition (TA) space. You get the opportunity to work on a ground up rebuild of our analytical capabilities, from data ingress, to complex business transformations to end user reporting and beyond. In this role, you will invent and build on behalf of candidates, experiment and test new ideas, evangelize successes, and drive consistency.The ideal candidate is an independent Data Scientist who can source data, cleanse, analyze, refine, enrich, model, present, automate and document our business data pipelines. You will always be on the lookout for ways to optimize the information flow process, stay on top of latest trends in data warehousing and be able to coordinate and work on multiple, related projects.Responsibilities:· Collaborate with recruiting operations, data scientists, and business leaders to define business processes and provide analytical support· Leverage code to analyze complex datasets and design, develop and evaluate data transformations to solve specific business problems· Build scalable, efficient, and automated data processes to facilitate customer-facing reporting· Automate TA processes to streamline business operations· Communicate verbally or in writing to business customers / leadership to sharing insights and recommendationsThis role can be based out of any US/Canada AWS Corporate location (i.e. Seattle, WA, Arlington, VA, Herndon, VA, New York, NY, Boston, MA, Chicago, IL, Dallas, TX, Cupertino, CA, Palo Alto, CA).
LU, Luxembourg
At Amazon, we strive to be the most innovative and customer centric company on the planet. Come work with us to develop innovative Customer Fulfilment products, tools and research driven solutions in a fast-paced environment by collaborating with smart and passionate leaders, program managers, data scientists and software developers. Our mission is to build the most efficient, intelligent and interpretable solutions on the planet.The EU Ops Integration Analytics team is part of Amazon EU Customer Fulfillment and is responsible for improving and supporting performance management of our Fulfilment Centers through state-of-the-art and scalable analytics solutions. We work backwards from the customer and define new innovative solutions that raise the bar on customer experience whilst constantly lowering our cost and supporting our continued growth.We are looking for a thought leader and you demonstrate this by delivering solutions, not just by having ideas. We encourage you to shape the business with data driven recommendations. A successful candidate has an entrepreneurial spirit and wants to make a big impact. You will develop strong working relationships and thrive in a collaborative team environment. Your role requires the ability to influence and interact with broad range of stakeholders (technical and non-technical). You draw from a broad data science expertise to mentor Data Scientists and Business Intelligence Engineers; following a rigorous scientific methodology, while providing leadership on complex analytical topics. You provide guidance on cutting-edge methods in big data processing, data science literature, experimentation and careful consideration of modeling decisions. We expect you to have breadth of data science knowledge, and depth in predictive modeling (supervised learning) and unsupervised learning (clustering).Key Responsibilities· Develop predictive models and decision science to guide program and operations teams on improving our customer experience (e.g. predicting concessions and optimizing the best action to take, sustainability and energy etc.)· Drive data science best practices and mentoring junior team members based on your in-depth knowledge in theoretical and practical data science disciplines.· Proactively seek to identify business opportunities and provide solutions based on a broad and deep knowledge of Amazon’s data resources, industry best-practices, and work done by other teams.· Partner with, coordinate, and influence multiple teams outside of EU Customer Fulfillment (Customer Service, Transportation, Amazon Logistics.), to support key initiatives.· Be the voice of the customer (end customer and data consumer), aligning stakeholders with scalable mechanisms to incorporate our models into product and engineering decision-making processes.· Drive and promote experimentation culture (e.g. A/B testing) with data-driven mindset and measurable approach.
GB, London
Come build the future of entertainment with us. Are you interested in shaping the future of movies and television? Do you want to define the next generation of how and what Amazon customers are watching?Prime Video is a premium streaming service that offers customers a vast collection of TV shows and movies - all with the ease of finding what they love to watch in one place. We offer customers thousands of popular movies and TV shows from Originals and Exclusive content to exciting live sports events. We also offer our members the opportunity to subscribe to add-on channels which they can cancel at anytime and to rent or buy new release movies and TV box sets on the Prime Video Store. Prime Video is a fast-paced, growth business - available in over 240 countries and territories worldwide. The team works in a dynamic environment where innovating on behalf of our customers is at the heart of everything we do. If this sounds exciting to you, please read on.The Research & Insight team operates in a dynamic and entrepreneurial environment across Europe and the world to understand our customers holistically. We work with senior stakeholders across a wide range of functions to plan, execute, and deliver continuous knowledge and insight to marketing and business teams to deliver customer centric growth.We are looking for a Sr. Data Scientist, Market Research to build our data strategy from the ground up. In this role, you will define quantitative research data standards and structures for end-to-end research processes, ensuring fit for purpose databases that are widely accessible and in usable formats for a variety of stakeholders. You will architect tools such as dashboards and automated reporting to help democratize our market research data. You’ll leverage predictive models, advanced machine learning/AI capabilities and exploratory data analysis (EDA) to solve problems and deliver insight.Responsibilities· Collecting and structuring data from a variety of 3P agency partners and APIs.· Collaborate closely with research, marketing, finance and content partner teams to ensure your data roadmap is fit for purpose across stakeholder groups.· Define and develop data management platforms, analysis tools and user friendly dashboards and reports.· Conduct ad-hoc analysis and predictive modelling to extract value from data to uncover opportunities and recommend actions.· Visualize data sets to inspire stakeholders (word clouds, infographics).· Perform regular data and system audits and feedback to ensure complete, accurate and usable data.· Optimize self-serve platform for data reporting and analysis to accelerate information-to-action at scale.· Build capability training across data and tools.· An SME for research data platform tools and analysis capabilities and delivery.
US, WA, Seattle
Amazon Advertising is one of Amazon's fastest growing and most profitable businesses, responsible for defining and delivering a collection of advertising products that drive discovery and sales. Our products are strategically important to our Retail and Marketplace businesses driving long term growth. We deliver billions of ad impressions and millions of clicks daily and are breaking fresh ground to create world-class products.Worldwide Ad Success team (WASE) is at the forefront of our amazing growth machine enabling our teams to deliver at scale. Our goal is to scale account management multifold by investing in strategic self-service applications that improve productivity of external advertising customers and internal account management executives. We are highly motivated, collaborative and fun-loving with an entrepreneurial spirit and bias for action. With a broad mandate to experiment and innovate, we are growing at an unprecedented rate with a seemingly endless range of new opportunities.As part of our team evolution we are investing in improving our understanding of the advertisers on Amazon through advanced ML modeling and building an ML service that delivers recommendations to advertisers and solves the prioritization and selection of most optimum recommendations and measure impact with explain-ability.We are moving fast and have the ability to shape our tech infrastructure that will combine science and scalable engineering at a rapid pace. We are looking for a senior Applied Scientist to join the team to drive key science methods and delivery of the project, working closely with product and engineering leads, as well as our leadership. This is a relatively new team, with a focused initiative. We’re a fast-growing team with high visibility from the leadership team and lots of new opportunities.As an Applied Scientist on this team you will:· Solve business problems using state of the art machine learning methods.· Work on full life-cycle projects - from researching the optimal machine learning models to use to deploying your models into production.· Drive processes, tools, and statistical methods that support rational decision-making.· Be technically fearless: You aren't satisfied by performing 'as expected' and push the tech teams past conventional boundaries. Your dial goes to '11'.· Help grow recruit other scientists to achieve outstanding results.· Foster a creative atmosphere to let engineers and other PMs innovate, while holding them accountable for making smart decisions and delivering results.· Explore new problem spaces with unique constraints and thus non-obvious solutions; identify any gaps in the solutions and/or approach.Why you love this opportunityAmazon is investing heavily in building a world-class advertising business. We are responsible for defining and delivering a collection of self-service performance advertising products that drive discovery and sales. Our products are strategically important to our Retail and Marketplace businesses driving long-term growth. We deliver billions of ad impressions and millions of clicks daily and break fresh ground to create world-class products. We are highly motivated, collaborative, and fun-loving team with an entrepreneurial spirit. With a broad mandate to experiment and innovate.Impact and Career GrowthYou will invent new shopper and advertiser experiences and influence customer-facing shopping experiences to help suppliers grow their retail business and the auction dynamics that leverage native advertising; this is your opportunity to work within the fastest-growing businesses across all of Amazon. Define a long-term science vision for our advertising business, driven fundamentally from our customers' needs, translating that direction into specific plans for research and applied scientists, as well as engineering and product teams. This role combines science leadership, organizational ability, technical strength, product focus, and business understanding.Team video https://youtu.be/zD_6Lzw8raEAmazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us
US, VA, Arlington
Amazon Global Talent Management (GTM) Science is an innovative organization that exists to propel Amazon HR towards being the most scientific HR organization on earth. The GTM Science mission is to use Science to assist and measurably improve every talent decision made at Amazon. We do this by discovering signals in workforce data, deploying statistical models into Amazon’s talent products, and guiding the broader GTM team to pursue high-impact opportunities with tangible returns. This multi-disciplinary approach spans capabilities, including: data engineering, reporting and analytics, research and behavioral sciences, and applied sciences such as economics and machine learning.We are seeking a Senior Research Scientist with deep quantitative and qualitative research expertise in Diversity, Equity, and Inclusion (DEI) and the Future of Work (FoW). This person will possess a strong mixed methods background, knowledge of different approaches to evaluating fairness in employment decisions, and experience with analyzing DEI data. In this role you will:· Design, develop, and execute quantitative and qualitative data collection methods in future of work, DEI, and related talent management efforts· Conduct quantitative analyses of DEI data and trends· Conduct qualitative data collection and analysis· Partner closely with Amazon Global DEI teams· Partner closely and drive effective collaborations across multi-disciplinary research and product teams· Manage full life cycle of large scale research programs related to DEI
US, CA, East Palo Alto
MULTIPLE POSITIONS AVAILABLEEntity: Amazon Web Services, Inc., an Amazon.com CompanyTitle: Applied Scientist IILocation: East Palo Alto, CAPosition Responsibilities:Participate in the design, development, evaluation, deployment and updating of data-driven models and analytical solutions for machine learning (ML) and/or natural language (NL) applications. Develop and/or apply statistical modeling techniques (e.g. Bayesian models and deep neural networks), optimization methods, and other ML techniques to different applications in business and engineering. Routinely build and deploy ML models on available data. Research and implement novel ML and statistical approaches to add value to the business. Mentor junior engineers and scientists.Amazon.com is an Equal Opportunity-Affirmative Action Employer - Minority / Female / Disability / Veteran / Gender Identity / Sexual Orientation.#0000
US, WA, Seattle
We are a passionate team working to build a best-in-class healthcare product designed to make high-quality healthcare easy to access.We are looking for a truly innovative and technically strong applies scientist with a background in machine learning and natural language understanding.As a Senior Applied Scientist, you will:· develop models for various natural language processing tasks, including named-entity recognition, natural language inference, sentiment analysis, text summarization, and question answering within in a healthcare context· work closely with product managers to expand the depth of our product insights with data, create a variety of experiments, and determine the highest-impact projects to include in planning roadmaps· provide technical and scientific guidance to your team members· ensure that teams are collecting, understanding, and using data to inform every decision that impacts our customers· stay current with advancements and the latest modeling techniques in the field· publish your research findings in top conferences and journalsAbout You:· Problem Solver: Ability to utilize exceptional problem-solving skills to work through different challenges in ambiguous situations.· Doer: You’ve successfully delivered end-to-end AI/ML projects, working through conflicting viewpoints and data limitations.· Detail Oriented: You have an enviable level of attention to details, and catch things that others miss.· Communicator: Ability to communicate analytical results to senior leaders, peers, and external customers.· Influencer: Innovative scientist with the ability to identify opportunities in a fast-paced and ever-changing environment, and gain support with data and storytelling.Here at Amazon Care, we embrace our differences. We are committed to furthering our culture of inclusion. 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.Our team also puts a high value on work-life balance. Striking a healthy balance between your personal and professional life is crucial to your happiness and success here, which is why we aren’t focused on how many hours you spend at work or online. Instead, we’re happy to offer a flexible schedule so you can have a more productive and well- balanced life—both in and outside of work.Amazon is committed to a diverse and inclusive workforce. Amazon is an equal opportunity employer and does not discriminate on the basis of race, ethnicity, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us.
US, NY, New York
Sponsored Products (SP) is Amazon's largest and fastest growing ad business. SP ads are shown prominently throughout search and product detail pages and allow shoppers to seamlessly discover products sold on Amazon. These are native ads that appear visually similar to other content on the page, which presents a huge opportunity for growth and impact, but also a significant responsibility to protect shopper experience.Job Responsibilities:· Design, develop, and deploy machine learning solutions.· Conduct hands-on data analysis, build large-scale machine-learning models and pipelines.· Work closely with software engineers on detailed requirements, technical designs and implementation of end-to-end solutions in production.· Run regular A/B experiments, gather data, perform statistical analysis, and communicate the impact to senior leaders.· Establish scalable, efficient, automated processes for large-scale data analysis, machine-learning model development, model validation and serving.· Provide technical leadership, research new machine learning approaches to drive continued scientific innovation.· Be a member of the Amazon-wide Machine Learning Community, participating in internal and external MeetUps, Hackathons and Conferences.Impact and Career Growth:· Opportunity to grow and broaden your machine learning skills a make impact – the work you deliver directly impacts customers and revenue!· Work in an environment that thrives on creativity, experimentation, and product innovation.· Drive real-time algorithms to allocate billions of ads per day in advertising auctions.· Have the ability to experiment autonomously with meaningful projects.· Mentor others.Why you love this opportunity:Amazon is investing heavily in building a world class advertising business and we are responsible for defining and delivering a collection of self-service performance advertising products that drive discovery and sales. Our products are strategically important to our Retail and Marketplace businesses driving long term growth. We deliver billions of ad impressions and millions of clicks daily and are breaking fresh ground to create world-class products. We are highly motivated, collaborative and fun-loving with an entrepreneurial spirit and bias for action. With a broad mandate to experiment and innovate, we are growing at an unprecedented rate with a seemingly endless range of new opportunities.
SG, Singapore
The Amazon Prime Team is hiring Interns in Economics. We are looking for detail-oriented, organized, and responsible individuals who are eager to learn how to apply economic and econometric theories to large-scale business problems and big data sets.These are full-time positions at 40 hours per week, with compensation being awarded on an hourly basis. You will work in a team of economists, data scientists, and engineers and in collaboration with product and finance managers. These experiences will translate well into writing applied chapters in your dissertation and prepare you with placement in academia or private sector.Roughly 50% of research assistants from previous cohorts have converted to full time data science or economics employment at Amazon. If you are interested, please send your CV to our mailing list at econ-internship@amazon.com.
US, WA, Seattle
Interested in using AI to improve the shopping experience of millions of customers? Amazon Search has the perfect job for you.Amazon Search Customer Experience is looking for an experienced scientist to lead the innovation in Search Whole Page Optimization (WPO). Your research spans deep learning, reinforcement learning, and personalized recommendations. You will work with a team of scientists and engineers to make Amazon’s search experience intelligent, intuitive, and enjoyable.A successful candidate has strong customer obsession, highly-cited publications in relevant areas, and a track record of deploying research outcomes in production. You will bring deep technical expertise and strong business acumen. Amazon leaders are visionaries who are not afraid of rolling up their sleeves and getting their hands dirty. You will help shape the future of Amazon’s search customer experience by painting a compelling vision and leading the journey to get there. You must have the desire to make industry-wide impact and the ability to work within a fast moving environment to rapidly deliver innovations.As a senior leader, you will be responsible for the holistic optimization of Amazon search pages. From page layout to content ranking, from the navigation experience to product display optimization, you will rethink the assumptions behind traditional e-commerce experience and leverage AI to make the shopping journey of each customer a delightful one. You will be part of the Search technical leadership community that forms the backbone of the company. You will play a critical role in business planning, work closely with senior executives, and influence our long-term technical and business strategy.If you like the challenges and opportunities in this exciting space, come join us to work hard, have fun, and make history.
US, WA, Seattle
The Amazon Shipping is hiring Interns in Economics. We are looking for detail-oriented, organized, and responsible individuals who are eager to learn how to apply what they've learned in an academic setting to a business environment, specifically focused on time series forecasting for routing problems.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, please send your CV 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
US, WA, Seattle
Amazon is looking for a creative Senior Research Scientist to tackle some of the most interesting problems on the leading edge of natural language processing (NLP), machine learning (ML), search and related areas with our Alexa AI team. Alexa AI aims to reinvent search and information retrieval for a voice-forward, multi-modal future. It enables customers to interact with unstructured and semi-structured content via a broad range of technologies including question answering, summarization, search, and multi-turn dialogues.If you are looking for an opportunity to solve deep technical problems and build innovative solutions in a fast-paced environment working within a smart and passionate team, this might be the role for you. You will develop and implement novel scalable algorithms and modeling techniques to advance the state-of-the-art in technology areas at the intersection of ML, NLP, search, and deep learning. You will innovate, help move the needle for research in these exciting areas and build cutting-edge technologies that enable delightful experiences for hundreds of millions of people.In this role you will:· Work collaboratively with other scientists and developers to design and implement scalable models for accessing and presenting information;· · Drive scalable solutions from the business to prototyping, production testing and through engineering directly to production;· · Drive best practices on the team, deal with ambiguity and competing objectives, and mentor and guide junior members to achieve their career growth potential.