How three science PhDs found different career paths at Amazon

Their doctoral degrees help these product managers bridge the gap between business and science.

While most students get into science PhD programs envisioning a career in research, there are many other paths to pursue. At Amazon, employees with advanced degrees in science find roles in product and program management, and other careers that depart from the traditional academic route.

The choice is not as unusual as you might think. Almost 40% of U.S. doctoral scientists and engineers who are employed describe their primary or secondary work activity as “management, sales or administration,” according to the 2017 Survey of Doctorate Recipients conducted by the National Center for Science and Engineering Statistics.

Tingting Sha Irene Song Ahmed El Saadany Amazon Science.jpg
Left to right: Tingting Sha, senior manager; Irene Song, principal product manager; and Ahmed El Saadany, senior product manager; all three are scientists who have migrated to product management roles within Amazon's Supply Chain Optimization Technologies (SCOT) organization. Each says their science credentials help them influence the development of new products and services.

Nor does working in one of those areas mean leaving behind all the training they received while obtaining their advanced degrees.

Individuals who persevere through an arduous PhD program develop the ability to think deeply about problems and develop solutions for them, a skill that is crucial for product managers.

“The mental model and the foundational skill sets are the same,” said Tingting Sha, senior manager at Amazon Supply Chain Optimization Technologies (SCOT). “How do we look at a problem? How do we use a scientific solution to address that problem and better serve our customers? All the learnings I had with my PhD are applicable to answer those questions.”

Sha is not the only scientist turned product manager. We spoke with her, Irene Song, principal product manager, and Ahmed El Saadany, senior product manager, about their science backgrounds and what motivated them to pursue a career in industry.

Literature, finance, advertising: Irene Song’s non-traditional background

As an undergrad at Smith College, Song never contemplated working in the tech industry or even following a science-related career. She wanted to be a writer.

“My plan was to go to grad school and study literature,” she says.

When she finished her bachelor’s degree in literature and math and got a job offer from an investment bank, she decided to work for a couple of years before following her literary path. She ended up enjoying finance and decided to apply for an MS/PhD program in financial engineering at Columbia University. It was 2008, and her manager advised her that it made sense to take a break and go to grad school given the financial crisis.

I always liked observing what people are doing to make business decisions and then figuring out a way to automate that based on data.
Irene Song

When Song finished her PhD, which focused on portfolio optimization, she knew she didn’t want to remain in academia because she didn’t enjoy conducting research in isolation. But she also didn’t want to go back to finance. After attending a talk about how the advertising industry was going digital, she became interested in applying her portfolio optimization experience in advertising.

For three years she worked for an advertising agency technology team, developing a platform to help clients determine how to invest advertising funds in an optimal way. She was responsible for connecting business, science, and technology.

“What I realized through working in different industries is that I always liked observing what people are doing to make business decisions and then figuring out a way to automate that based on data and so we can make decisions more rationally in a scalable manner,” she said.

As she described her interests to a friend who had gone to work for Amazon, he told her that they aligned with the description of a product manager role. She then had a call with an Amazon manager, which turned into a successful job interview. The fact that her team makes business decisions while also owning the technology used to implement scientific solutions made the job a great fit for her, Song said. It also fulfilled her interest of automating solutions at scale.

Today she works across multiple teams to develop solutions for several types of opportunities, serving as a bridge between business, science, and engineering. Recently, for example, she and her team developed a proposal to assess inventory capacity at warehouses during holidays. Taking lessons learned during the 2020 holiday season around capacity and inventory volume, her team is working to adapt in preparation for this year’s holidays.

Ahmed El Saadany moved to industry for “real world” experiences

El Saadany was following a successful academic path in the field of supply chain management. A few of his research papers, which in general looked into how to preserve the environment while also improving the supply chain, got hundreds of citations. One of the projects he worked on during his PhD at Ryerson University in Canada focused on determining effective incentives for customers to return products that they no longer use so they can be sold again or recycled.

Even as a scientist, not just as an engineer, I realized I’d learn more by working in industry, especially when it comes to supply chain
Ahmed El Saadany

At one point in his academic trajectory, his models became very complicated. He felt he was relying on too many assumptions and that it wouldn’t be fruitful to continue producing increasingly complex models without observing how things worked in the “real world”.

“Even as a scientist, not just as an engineer, I realized I’d learn more by working in industry, especially when it comes to supply chain,” he said.

El Saadany joined Amazon in January 2016 after working in consulting for a few years. “One of the things that I found similar between academia and Amazon is that you have the chance and the time to do a really deep dive into one area — to understand all the details about it,” he said.

At Amazon, El Saadany and his team assess situations where, for example, Amazon ends up with more inventory than is needed.

“In these instances, we need to either improve the sales, offer a discount, market it in a different way, or work with the vendor to make sure that we have a very efficient and agile supply chain,” he said. “Because if we keep that product forever in our inventory, it will lose value, and it won’t help our customers. So, the question is, ‘How can we better serve our customers and maximize the value of the product?’”

El Saadany notes that the product manager role is the right fit for researchers who want to build on what they’ve learned as scientists and develop tools that help people directly.

“When you build something within Amazon, you can see the impact of your work as an Amazon delivery arrives on your doorstep,” he said.

Tinting Sha’s trajectory: From designing CPUs to leading a team of 25 people

Like El Saadany, one reason Sha decided to move into industry was that she felt the assumptions made in academia did not always correspond to reality.

“I wanted to understand what it was like to get more realistic, because research might go so off the track when you don't know the business context,” she said.

She also wanted to see her research have real-world impact.

Keep learning and being curious, there’s always going to be a learning process.
Tingting Sha

For her PhD, Sha studied computer architecture at the University of Pennsylvania. Back in college, she was fascinated by how central processing units (CPUs) processed so many different types of information. That’s why going to UPenn — where ENIAC was developed — was a straightforward decision. In her research, she focused on how to store and retrieve data more efficiently.

While her initial plan was to become an academic, her life’s journey took a new path after an internship at Intel.

“Over time, I determined that my true passion is trying to build something that's going to help my target customers,” said Sha. “And in order to do so, I needed to equip myself not only with science and engineering capabilities, but also with the business aspects.”

That's why she obtained a master’s in business administration from the Massachusetts Institute of Technology in 2015, and then joined Amazon.

Although she doesn’t design CPUs anymore, Sha said the problem-solving abilities harnessed during her PhD studies at UPenn are in constant use. Since joining Amazon, she continues to learn new skills required for her senior manager, product manager role.

Her philosophy: “Keep learning and being curious,” she says. “There’s always going to be a learning process.” Right now, as she leads a team of 25 people, she’s focused on growing her skills as a leader.

Impacting science as a product manager

For Song, El Saadany, and Sha, their science credentials help them influence the development of new products and services.

“At Amazon, you end up doing something at the forefront of science, as a lot of what we do is not actually published out there,” El Saadany said. “We're building new things because we're serving customers in ways that have never been done before.”

The reason why scientists feel comfortable writing a science proposal with me is that they know that, when I’m editing it, I understand what’s in the proposal.
Irene Song

“The reason why scientists feel comfortable writing a science proposal with me is that they know that, when I’m editing it, I understand what’s in the proposal,” said Song. “Basically, it reduces the gap of communication between people with different backgrounds.”

One bit of career advice she has for scientists aspiring to a product manager position is to focus on communication skills.

“If you want to be in the product role, more than understanding science, you must be able to communicate what the problem is — and what the solution is — to various audiences, regardless of their backgrounds.”

Sha says SCOT teams are always looking for “Amazonians currently not working at Amazon.” By that she means individuals who have a strong sense of ownership and who make good judgements in both diving deep on a topic, and thinking big.

“You need to both zoom into the details and really understand the problem, while also popping up to see the bigger picture.”

Related content

US, VA, Arlington
Do you want a role with deep meaning and the ability to have a global impact? Hiring top talent is not only critical to Amazon’s success – it can literally change the world. It took a lot of great hires to deliver innovations like AWS, Prime, and Alexa, which make life better for millions of customers around the world. As part of the Intelligent Talent Acquisition (ITA) team, you'll have the opportunity to reinvent Amazon’s hiring process with unprecedented scale, sophistication, and accuracy. ITA is an industry-leading people science and technology organization made up of scientists, engineers, analysts, product professionals, and more. Our shared goal is to fairly and precisely connect the right people to the right jobs. Last year, we delivered over 6 million online candidate assessments, driving a merit-based hiring approach that gives candidates the opportunity to showcase their true skills. Each year we also help Amazon deliver billions of packages around the world by making it possible to hire hundreds of thousands of associates in the right quantity, at the right location, at exactly the right time. You’ll work on state-of-the-art research with advanced software tools, new AI systems, and machine learning algorithms to solve complex hiring challenges. Join ITA in using cutting-edge technologies to transform the hiring landscape and make a meaningful difference in people's lives. Together, we can solve the world's toughest hiring problems. Within ITA, the Global Hiring Science (GHS) team designs and implements innovative hiring solutions at scale. We work in a fast-paced, global environment where we use research to solve complex problems and build scalable hiring products that deliver measurable impact to our customers. We are seeking selection researchers with a strong foundation in hiring assessment development, legally-defensible validation approaches, research and experimental design, and data analysis. Preferred candidates will have experience across the full hiring assessment lifecycle, from solution design to content development and validation to impact analysis. We are looking for equal parts researcher and consultant, who is able to influence customers with insights derived from science and data. You will work closely with cross-functional teams to design new hiring solutions and experiment with measurement methods intended to precisely define exactly what job success looks like and how best to predict it. Key job responsibilities What you’ll do as a GHS Research Scientist: • Design large-scale personnel selection research that shapes Amazon’s global talent assessment practices across a variety of topics (e.g., assessment validation, measuring post-hire impact) • Partner with key stakeholders to create innovative solutions that blend scientific rigor with real-world business impact while navigating complex legal and professional standards • Apply advanced statistical techniques to analyze massive, diverse datasets to uncover insights that optimize our candidate evaluation processes and drive hiring excellence • Explore emerging technologies and innovative methodologies to enhance talent measurement while maintaining Amazon's commitment to scientific integrity • Translate complex research findings into compelling, actionable strategies that influence senior leader/business decisions and shape Amazon's talent acquisition roadmap • Write impactful documents that distill intricate scientific concepts into clear, persuasive communications for diverse audiences, from data scientists to business leaders • Ensure effective teamwork, communication, collaboration, and commitment across multiple teams with competing priorities A day in the life Imagine diving into challenges that impact millions of employees across Amazon's global operations. As a GHS Research Scientist, you'll tackle questions about hiring and organizational effectiveness on a global scale. Your day might begin with analyzing datasets to inform how we attract and select world-class talent. Throughout the day, you'll collaborate with peers in our research community, discussing different research methodologies and sharing innovative approaches to solving unique personnel challenges. This role offers a blend of focused analytical time and interacting with stakeholders across the globe.
US, WA, Seattle
We are looking for a researcher in state-of-the-art LLM technologies for applications across Alexa, AWS, and other Amazon businesses. In this role, you will innovate in the fastest-moving fields of current AI research, in particular in how to integrate a broad range of structured and unstructured information into AI systems (e.g. with RAG techniques), and get to immediately apply your results in highly visible Amazon products. If you are deeply familiar with LLMs, natural language processing, computer vision, and machine learning and thrive in a fast-paced environment, this may be the right opportunity for you. Our fast-paced environment requires a high degree of autonomy to deliver ambitious science innovations all the way to production. You will work with other science and engineering teams as well as business stakeholders to maximize velocity and impact of your deliverables. It's an exciting time to be a leader in AI research. In Amazon's AGI Information team, you can make your mark by improving information-driven experience of Amazon customers worldwide!
US, MA, N.reading
Amazon Industrial Robotics is seeking exceptional talent to help develop the next generation of advanced robotics systems that will transform automation at Amazon's scale. We're building revolutionary robotic systems that combine cutting-edge AI, sophisticated control systems, and advanced mechanical design to create adaptable automation solutions capable of working safely alongside humans in dynamic environments. This is a unique opportunity to shape the future of robotics and automation at unprecedented scale, working with world-class teams pushing the boundaries of what's possible in robotic manipulation, locomotion, and human-robot interaction. This role presents an opportunity to shape the future of robotics through innovative applications of deep learning and large language models. At Amazon Industrial Robotics we leverage advanced robotics, machine learning, and artificial intelligence to solve complex operational challenges at unprecedented scale. Our fleet of robots operates across hundreds of facilities worldwide, working in sophisticated coordination to fulfill our mission of customer excellence. We are pioneering the development of robotics foundation models that: - Enable unprecedented generalization across diverse tasks - Enable unprecedented robustness and reliability, industry-ready - Integrate multi-modal learning capabilities (visual, tactile, linguistic) - Accelerate skill acquisition through demonstration learning - Enhance robotic perception and environmental understanding - Streamline development processes through reusable capabilities The ideal candidate will contribute to research that bridges the gap between theoretical advancement and practical implementation in robotics. You will be part of a team that's revolutionizing how robots learn, adapt, and interact with their environment. Join us in building the next generation of intelligent robotics systems that will transform the future of automation and human-robot collaboration. Key job responsibilities As an Applied Science Manager in the Foundations Model team, you will: - Build and lead a team of scientists and developers responsible for foundation model development - Define the right ‘FM recipe’ to reach industry ready solutions - Define the right strategy to ensure fast and efficient development, combining state of the art methods, research and engineering. - Lead Model Development and Training: Designing and implementing the model architectures, training and fine tuning the foundation models using various datasets, and optimize the model performance through iterative experiments - Lead Data Management: Process and prepare training data, including data governance, provenance tracking, data quality checks and creating reusable data pipelines. - Lead Experimentation and Validation: Design and execute experiments to test model capabilities on the simulator and on the embodiment, validate performance across different scenarios, create a baseline and iteratively improve model performance. - Lead Code Development: Write clean, maintainable, well commented and documented code, contribute to training infrastructure, create tools for model evaluation and testing, and implement necessary APIs - Research: Stay current with latest developments in foundation models and robotics, assist in literature reviews and research documentation, prepare technical reports and presentations, and contribute to research discussions and brainstorming sessions. - Collaboration: Work closely with senior scientists, engineers, and leaders across multiple teams, participate in knowledge sharing, support integration efforts with robotics hardware teams, and help document best practices and methodologies.
CA, QC, Montreal
Join the next revolution in robotics at Amazon's Frontier AI & Robotics team, where you'll work alongside world-renowned AI pioneers to push the boundaries of what's possible in robotic intelligence. As an Applied Scientist, you'll be at the forefront of developing breakthrough foundation models that enable robots to perceive, understand, and interact with the world in unprecedented ways. You'll drive independent research initiatives in areas such as perception, manipulation, scene understanding, sim2real transfer, multi-modal foundation models, and multi-task learning, designing novel algorithms that bridge the gap between state-of-the-art research and real-world deployment at Amazon scale. In this role, you'll balance innovative technical exploration with practical implementation, collaborating with platform teams to ensure your models and algorithms perform robustly in dynamic real-world environments. You'll have access to Amazon's vast computational resources, enabling you to tackle ambitious problems in areas like very large multi-modal robotic foundation models and efficient, promptable model architectures that can scale across diverse robotic applications. Key job responsibilities - Design and implement novel deep learning architectures that push the boundaries of what robots can understand and accomplish - Drive independent research initiatives in robotics foundation models, focusing on breakthrough approaches in perception, and manipulation, for example open-vocabulary panoptic scene understanding, scaling up multi-modal LLMs, sim2real/real2sim techniques, end-to-end vision-language-action models, efficient model inference, video tokenization - Lead technical projects from conceptualization through deployment, ensuring robust performance in production environments - Collaborate with platform teams to optimize and scale models for real-world applications - Contribute to the team's technical strategy and help shape our approach to next-generation robotics challenges A day in the life - Design and implement novel foundation model architectures, leveraging our extensive compute infrastructure to train and evaluate at scale - Collaborate with our world-class research team to solve complex technical challenges - Lead technical initiatives from conception to deployment, working closely with robotics engineers to integrate your solutions into production systems - Participate in technical discussions and brainstorming sessions with team leaders and fellow scientists - Leverage our massive compute cluster and extensive robotics infrastructure to rapidly prototype and validate new ideas - Transform theoretical insights into practical solutions that can handle the complexities of real-world robotics applications About the team At Frontier AI & Robotics, we're not just advancing robotics – we're reimagining it from the ground up. Our team is building the future of intelligent robotics through ground breaking foundation models and end-to-end learned systems. We tackle some of the most challenging problems in AI and robotics, from developing sophisticated perception systems to creating adaptive manipulation strategies that work in complex, real-world scenarios. What sets us apart is our unique combination of ambitious research vision and practical impact. We leverage Amazon's massive computational infrastructure and rich real-world datasets to train and deploy state-of-the-art foundation models. Our work spans the full spectrum of robotics intelligence – from multimodal perception using images, videos, and sensor data, to sophisticated manipulation strategies that can handle diverse real-world scenarios. We're building systems that don't just work in the lab, but scale to meet the demands of Amazon's global operations. Join us if you're excited about pushing the boundaries of what's possible in robotics, working with world-class researchers, and seeing your innovations deployed at unprecedented scale.
US, NY, New York
The Sponsored Products and Brands team at Amazon Ads is re-imagining the advertising landscape through cutting-edge generative AI technologies, revolutionizing how millions of customers discover products and engage with brands across Amazon.com and beyond. We are at the forefront of re-inventing advertising experiences, bridging human creativity with artificial intelligence to transform every aspect of the advertising lifecycle from ad creation and optimization to performance analysis and customer insights. We are a passionate group of innovators dedicated to developing responsible and intelligent AI technologies that balance the needs of advertisers, enhance the shopping experience, and strengthen the marketplace. If you're energized by solving complex challenges and pushing the boundaries of what's possible with AI, join us in shaping the future of advertising. Key job responsibilities Participate in the Science hiring process as well as mentor other scientists - improving their skills, their knowledge of your solutions, and their ability to get things done. Identify and devise new video related solutions following a customer-obsessed scientific approach to address customer or business problems when the problem is ill-defined, needs to be framed, and new methodologies or paradigms need to be invented at the product level. Articulate potential scientific challenges of ongoing or future customers’ needs or business problems, and present interventions to address them. Independently assess alternative video related technologies, driving evaluation and adoption of those that fit best A day in the life As an Applied Scientist on the Sponsored Products Video team, you will work with a team of talented and experienced engineers, scientists, and designers to help bring new products to market and ensure that our customers are delighted by what we create. The Sponsored Products Video team is responsible for the design, development, and implementation of Sponsored Products Video experiences worldwide. About the team The Sponsored Products Video team within Sponsored Products and Brands creates relevant and engaging video experiences, connecting advertisers and shoppers. We are on a mission to make Amazon the best in class destination for shoppers to discover, engage and build affinity with brands, making shopping delightful, & personal.
IN, TS, Hyderabad
We're seeking an Applied Scientist to lead and innovate in applying advanced AI technologies that will reshape how businesses sell on Amazon. Our team is passionate about leveraging Machine Learning, GenAI, and Agentic AI to help B2B sellers optimize their operations and drive growth. Join Amazon Business 3P (Third Party - Sellers) - a rapidly growing global organization where we innovate at the intersection of AI technology and B2B commerce. We're reimagining how sellers reach and serve business customers, creating intelligent solutions that help them grow their B2B business on Amazon. From AI-powered Seller Central tools to smart business certifications, dynamic pricing capabilities, and advanced analytics, we're transforming how B2B selling happens. As an Applied Scientist II on our AB 3P Tech team, you'll drive the development and implementation of state-of-the-art algorithms and models for supervised fine-tuning and reinforcement learning. You'll work with highly technical, entrepreneurial teams to: - Design and implement AI models that power the B2B selling experience - Lead the development of GenAI products that can handle Amazon-scale use cases - Drive research and implementation of advanced algorithms for human feedback and complex reasoning - Make strategic AI technology decisions and mentor technical talent - Own critical AI systems spanning from Seller Central to Amazon Business detail pages Join us in shaping the future of B2B selling - we're building applied AI solutions that businesses love and trust for their day-to-day success. If you are scrappy and bias for action is your favorite Leadership Principle, you'll fit right in as we innovate across the seller experience to create significant impact in this fast-growing business. Key job responsibilities Key job responsibilities: - Collaborate with cross-functional teams of engineers, product managers, and scientists to identify and solve complex problems in Gen AI - Design and execute experiments to evaluate the performance of different algorithms and models, and iterate quickly to improve results - Think big about the arc of development of Gen AI over a multi-year horizon, and identify new opportunities to apply these technologies to solve real-world problems - Communicate results and insights to both technical and non-technical audiences About the team At Amazon Business Third Party (AB3P) Tech, we're revolutionizing B2B e-commerce by empowering sellers in the business marketplace. Our scope spans the complete B2B selling journey, from Seller Central to Amazon Business detail pages, cart, and checkout for merchant-fulfilled offers. Our entrepreneurial culture and global reach define us. We develop features across seller experience, delivery, certifications, fees, registration, and analytics, collaborating with worldwide teams and leveraging advanced AI technologies to continuously innovate. Working in true Day 1 spirit, we build next-generation solutions that shape the future of B2B commerce. Join us in building next-generation solutions that shape the future of B2B commerce.
GB, London
Come build the future of entertainment with us. Are you interested in shaping the future of movies and television? 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 including Amazon Originals and exclusive licensed content to exciting live sports events. Prime Video is a fast-paced, growth business - available in over 200 countries and territories worldwide. The Video Content Research team works in a dynamic environment where innovating on behalf of our customers is at the heart of everything we do. We are seeking a Data Scientist to develop scalable models that uncover key insights into how, why and when customers engage with Prime Video marketing. Key job responsibilities In this role you will work closely with business stakeholders and technical peers (data scientists, economists and engineers) to develop causal marketing measurement models, analyze experiments and investigate customer, marketing and content related factors that drive engagement with Prime Video. You will create mechanisms and infrastructure to deploy complex models and generate insights at scale. You will have the opportunity to work with large datasets, work with AWS to build and deploy machine learning models that impact Prime Video's marketing decisions. About the team The Video Content Research team uses machine learning, econometrics, and data science to optimize Amazon's marketing and content investments. We generate insights for Amazon's digital video strategy, partnering with finance, marketing, and content teams. We analyze customer behavior on Prime Video (marketing impressions, clicks on owned channels) to identify optimization opportunities.
US, MA, Boston
AI is the most transformational technology of our time, capable of tackling some of humanity’s most challenging problems. That is why Amazon is investing in generative AI (GenAI) and the responsible development and deployment of large language models (LLMs) across all of our businesses. Come build the future of human-technology interaction with us. We are looking for a Research Scientist with strong technical skills which includes coding and natural language processing experience in dataset construction, training and evaluating models, and automatic processing of large datasets. You will play a critical role in driving innovation and advancing the state-of-the-art in natural language processing and machine learning. You will work closely with cross-functional teams, including product managers, language engineers, and other scientists. Key job responsibilities Specifically, the Research Scientist will: • Ensure quality of speech/language/other data throughout all stages of acquisition and processing, including data sourcing/collection, ground truth generation, normalization, transformation, cross-lingual alignment/mapping, etc. • Clean, analyze and select speech/language/other data to achieve goals • Build and test models that elevate the customer experience • 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 • Work with engineers to develop efficient data querying infrastructure for both offline and online use cases
US, VA, Arlington
The People eXperience and Technology Central Science (PXTCS) team uses economics, behavioral science, statistics, and machine learning to proactively identify mechanisms and process improvements which simultaneously improve Amazon and the lives, wellbeing, and the value of work to Amazonians. PXTCS is an interdisciplinary team that combines the talents of science and engineering to develop and deliver solutions that measurably achieve this goal. PXTCS is looking for an economist who can apply economic methods to address business problems. The ideal candidate will work with engineers and computer scientists to estimate models and algorithms on large scale data, design pilots and measure impact, and transform successful prototypes into improved policies and programs at scale. PXTCS is looking for creative thinkers who can combine a strong technical economic toolbox with a desire to learn from other disciplines, and who know how to execute and deliver on big ideas as part of an interdisciplinary technical team. Ideal candidates will work in a team setting with individuals from diverse disciplines and backgrounds. They will work with teammates to develop scientific models and conduct the data analysis, modeling, and experimentation that is necessary for estimating and validating models. They will work closely with engineering teams to develop scalable data resources to support rapid insights, and take successful models and findings into production as new products and services. They will be customer-centric and will communicate scientific approaches and findings to business leaders, listening to and incorporate their feedback, and delivering successful scientific solutions. A day in the life The Economist will work with teammates to apply economic methods to business problems. This might include identifying the appropriate research questions, writing code to implement a DID analysis or estimate a structural model, or writing and presenting a document with findings to business leaders. Our economists also collaborate with partner teams throughout the process, from understanding their challenges, to developing a research agenda that will address those challenges, to help them implement solutions. About the team PXTCS is a multidisciplinary science team that develops innovative solutions to make Amazon Earth's Best Employer
US, WA, Bellevue
Amazon is looking for a Principal Applied Scientist world class scientists to join its AWS Fundamental Research Team working within a variety of machine learning disciplines. This group is entrusted with developing core machine learning solutions for AWS services. At the AWS Fundamental Research Team you will invent, implement, and deploy state of the art machine learning algorithms and systems. You will build prototypes and explore conceptually large scale ML solutions across different domains and computation platforms. You will interact closely with our customers and with the academic community. You will be at the heart of a growing and exciting focus area for AWS and work with other acclaimed engineers and world famous scientists. About the team About the team Diverse Experiences AWS values diverse experiences. Even if you do not meet all of the qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying. Why AWS? Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses. Inclusive Team Culture Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness. Mentorship & Career Growth We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional. Work/Life Balance We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud.