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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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. Key job responsibilities As a Senior Applied Scientist on this team, you will: • Lead a new initiative across Sponsored Products Bidding focused on AI/ML based features. • Be the technical leader in AI, Machine Learning; lead efforts within this team and across other teams. • Perform hands-on analysis and modeling of enormous data sets to develop insights that increase traffic monetization and merchandise sales, without compromising the shopper experience. • Drive end-to-end AI/Machine Learning projects that have a high degree of ambiguity, scale, complexity. • Build models, perform proof-of-concept, experiment, optimize, and deploy your models into production; work closely with software engineers to assist in productionizing your AI/ML models. • Run A/B experiments, gather data, and perform statistical analysis. • Establish scalable, efficient, automated processes for large-scale data analysis, machine-learning model development, model validation and serving. • Research new and innovative AI/ machine learning approaches. • Recruit Applied Scientists to the team and provide mentorship. A day in the life Why you will love this opportunity: Amazon is investing heavily in building a world-class advertising business. This team defines and delivers a collection of advertising products that drive discovery and sales. Our solutions generate billions in revenue and drive long-term growth for Amazon's Retail and Marketplace businesses. We deliver billions of ad impressions, millions of clicks daily, and break fresh ground to create world-class products. We are a highly motivated, collaborative, and fun-loving team with an entrepreneurial spirit - with a broad mandate to experiment and innovate. Impact and Career Growth: You will invent new 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 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. About the team The Sponsored Products and Brands team at Amazon Ads is re-imagining the advertising landscape through the latest 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. The SPB Bidding team within Sponsored Products and Brands is focused on guiding and supporting Millions of advertisers to meet their advertising needs of creating and managing ad campaigns. At this scale, the complexity of diverse advertiser goals, campaign types, and market dynamics creates both a massive technical challenge and a transformative opportunity: even small improvements in bidding systems can have outsized impact on advertiser success and Amazon’s retail ecosystem. Our vision is to build a highly personalized, context-aware bidding system that leverages auction simulations, ML models, and optimization algorithms. This framework, will operate across SPB bidding system and proactively delivering value based on deep understanding of the advertiser. To execute this vision, we collaborate closely with stakeholders across Ad Console, Sales, and Marketing to identify opportunities—from high-level product guidance down to granular recommendations—and deliver them through a tailored, personalized experience. Our work is grounded in state-of-the-art bidding agent architectures, tool integration, reasoning frameworks, and model customization approaches (including tuning and preference optimization), ensuring our systems are both scalable and adaptive.