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.”

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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.
IL, Tel Aviv
Come build the future of entertainment with us. Are you interested in helping shape the future of movies and television? Do you want to help 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 any time 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 We are seeking an exceptional Applied Scientist to join our Prime Video Sports personalization team in Israel. Our team is dedicated to developing state-of-the-art science to personalize the customer experience and help customers seamlessly find any live event in our selection. You will have the opportunity to work on innovative, large-scale projects that push the boundaries of what's possible in sports content delivery and engagement. Your expertise will be crucial in tackling complex challenges such as information retrieval, sequential modeling, realtime model optimizations, utilizing Large Language Models (LLMs), and building state-of-the-art complex recommender systems. Key job responsibilities We are looking for an Applied Scientist with domain expertise in Personalization, Information Retrieval, and Recommender Systems, or general ML to develop new algorithms and end-to-end solutions. As part of our team of applied scientists and software development engineers, you will be responsible for researching, designing, developing, and deploying algorithms into production pipelines. Your role will involve working with cutting-edge technologies in recommender systems and search. You'll also tackle unique challenges like temporal information retrieval to improve real-time sports content recommendations. As a technologist, you will drive the publication of original work in top-tier conferences in Machine Learning and Recommender Systems. We expect you to thrive in ambiguous situations, demonstrating outstanding analytical abilities and comfort in collaborating with cross-functional teams and systems. The ideal candidate is a self-starter with the ability to learn and adapt quickly in our fast-paced environment. About the team We are the Prime Video Sports team. In September 2018 Prime Video launched its first full-scale live streaming experience to world-wide Prime customers with NFL Thursday Night Football. That was just the start. Now Amazon has exclusive broadcasting rights to major leagues like NFL Thursday Night Football, Tennis majors like Roland-Garros and English Premier League to list a few and are broadcasting live events across 30+ sports world-wide. Prime Video is expanding not just the breadth of live content that it offers, but the depth of the experience. This is a transformative opportunity, the chance to be at the vanguard of a program that will revolutionize Prime Video, and the live streaming experience of customers everywhere.