What is a behavioral economist doing at Netflix?

Since launching the Master’s in Behavioral Economics at the University of Cyprus in 2022, we have received many inquiries from prospective students—most notably: “What exactly is behavioral economics?” and “What careers does it open up?”

Simply put, behavioral economics combines insights from economics and psychology to explain how people make everyday economic decisions—such as spending, saving, or valuing goods—while considering factors like emotions, habits, and how information is presented.

To shed light on the career possibilities, we recently hosted a fireside chat titled “What Is a Behavioral Economist Doing at Netflix?” featuring Dr. Andreas Aristidou, a Senior Data Scientist at Netflix. Born and raised in Cyprus, he shared his journey from studying economics in the UK and the US to working at major tech companies like Zillow and Netflix. His story demonstrated the practical impact behavioral economists can have across industries by leveraging a deep understanding of human behavior and decision-making.

Dr. Andreas Aristidou

In the interview that follows, I speak with Dr. Aristidou, whose insights mirror many of the themes explored during our event. From laying out the foundations of behavioral economics to highlighting its expanding influence on businesses, our conversation showcases why this field is generating so much excitement.

Your background is in economics. How did you first encounter behavioral economics, and what initially drew you to this field?

I remember back in high school deciding what I wanted to study in college. It was a battle between Economics which I had taken at high school, I really liked it and I was good at it, versus Psychology, that I had never taken a class of, but had always found extremely fascinating. As you know, I chose Economics at the time, and joined the University of Nottingham, completely oblivious to the fact that I was joining one of the leading universities in the area of behavioral economics. Not too long after I joined, I saw a course called “behavioral and experimental economics” which sounded very interesting and so I enrolled in my second year. That decision changed my whole career and life.

I will never forget the feeling I got at the end of the first lecture of that class. I felt like I had just witnessed the most interesting topic I had ever heard about in my life. The blend of economic principles with psychological insights, how different “strange” phenomena that we observe in our everyday lives can be explained and predicted by these behavioral patterns was fascinating to me. I remember things like increasing the sign-up rates for organ donation from low teens to almost 100% just by changing the framing of the question from opt-in to opt-out; that people tend to buy more stocks in sunny days because sun makes people feel more optimistic; or that a product becomes much more attractive when an irrelevant product that is worse is placed right next to it. I later remember how behavioral economics helped explain the findings from evolutionary game theoretic models like the tit-for-tat strategy in the repeated prisoners’ dilemma games.

I quickly became involved with assisting professors with their research, taking part in economic experiments and starting to craft my own ideas for behavioral economic experiments. That was my beginning in behavioral economics.

Many people associate behavioral economics with fun or quirky observations—great conversation starters at dinner parties—or with government “nudges” that promote healthier, more sustainable behaviors. Yet your career is in the private sector. Why do companies hire behavioral economists, and how do they benefit from these insights?

Behavioral economics tends to have this reputation in some circles but it's usually with outsiders who have little exposure to the field—perhaps they’ve read Thinking, Fast and Slow or another accessible pop-science book on cognitive biases. There can be a sense that it’s all about neat party tricks or government-led ‘nudge’ units. However, once you look under the hood, it’s not hard to see why the private sector is equally—even sometimes more—invested in behavioral insights.

Tech companies, for instance, operate in highly competitive environments where any slight edge can mean a tangible boost in market share or user retention. Small interventions—sometimes as subtle as how you structure a product’s onboarding flow or the wording in a purchase funnel—can have a powerful effect on customer behavior. Behavioral economics shines in revealing these levers of influence. It’s often about nudging users toward actions that are mutually beneficial: more user engagement and satisfaction on the one hand, and healthier revenue or conversion metrics on the other.

Behavioral economists bring a human-centered approach to product design, ensuring that user interfaces, messaging, and choice architecture align with how real people think and feel—rather than how spreadsheets suggest they ‘should.’ By recognizing that users have limited attention, rely on mental shortcuts, and sometimes misjudge risk, behavioral economists can design experiences that reduce friction, encourage transparency, and ultimately strengthen trust. This can be the difference between a product that frustrates users into churning and one that keeps them coming back.

Behavioral economics blends psychology and economics, while tech companies like Netflix or Zillow are largely data-driven. What does a behavioral economist do working as a Senior Data Scientist in such a company? In other words, how do you bridge these worlds? Can you share concrete examples of how behavioral economic principles are applied in a tech setting?

I don’t see behavioral economics as contradictory to being ‘data-driven.’ Quite the opposite. Large tech companies are constantly rolling out new features, pricing structures, and user experiences—but there are literally unlimited potential changes, interventions, or policies they might implement. You can’t test them all, or even think of them all, so you need a disciplined, theory-driven approach to focus on the most promising ideas.

That’s where behavioral economics comes in. It offers well-researched principles—like framing effects, social proof, or choice overload—that help companies target the specific user behaviors they want to influence. So, rather than throwing an entire box of spaghetti at the wall, a behavioral economist might throw just five or six strands—but those have a higher chance of sticking because they’re guided by evidence-based insights into how people actually make decisions.

At the same time, tech companies verify everything through data. Even if a hypothesis is grounded in a rock-solid theory, real-world behaviors can be influenced by industry context, cultural nuances, or interface design details. That’s why we run A/B tests, experiments, and observational studies to see if a proposed intervention truly benefits customers or moves core metrics. In other words, ‘trust, but verify.

Skeptics might say companies use behavioral insights primarily to manipulate customers and increase profits. How would you respond to that? Are there safeguards or ethical guidelines to ensure responsible use of behavioral science?

It’s a very valid concern, and not one that’s unique to behavioral economics. The same question arises in almost any field where there’s potential to influence people’s choices—advertising, marketing, even product design. Ultimately, it comes down to how individual companies, organizations, and practitioners choose to apply these insights.

A simple rule of thumb I like to use when evaluating whether a behavioral intervention is ethical is to ask: ‘Does this help people make more informed decisions?’ or ‘Does this intervention guide people toward choices that align with their own preferences and well-being?’ If the answer is yes, you’re probably on the right track.

Of course, there must also be broader structures in place—like industry standards, regulatory frameworks, and internal oversight bodies—to ensure these interventions aren’t exploitative. Responsible practitioners of behavioral science make transparency, consent, and user autonomy guiding principles. Yes, nudges might boost a company’s bottom line, but they can also help customers save money, reduce waste, or simply navigate complex choices more easily.

In other words, just because these insights can be misused doesn’t mean they must be. When applied ethically, behavioral economics can benefit both customers and companies—encouraging better-informed decision-making and building trust over the long run.

What unique perspectives do behavioral scientists bring to data science teams, and how do they enhance traditional data science skill sets? Also, do you see this dynamic changing with the rise of generative AI (genAI)?

Behavioral economists bring several core strengths to data science teams, starting with structured economic thinking—the ability to analyze incentives, market dynamics, and decision frameworks in a systematic way. They also excel at targeted hypothesis generation, drawing on well-established theories of human behavior to pinpoint which variables and interactions are most worth testing. A further advantage is experiment design and A/B testing. While most data teams run experiments, behavioral economists add rigor by focusing on why certain interventions might work and how best to measure real changes in user behavior. Finally, translating insights into policy or product interventions is often the critical piece: it’s one thing to discover a pattern in the data, but quite another to incorporate it ethically and effectively into product features, pricing, or user communications.

Now, with the rise of generative AI, the data science landscape is shifting quickly. GenAI is already excellent at coding, basic statistics, simulations, and even constructing machine learning models—areas that once required more human effort. However, it still struggles with deep contextual understanding of human emotions, nuanced decision-making, and domain-specific psychological or cultural insights. That’s precisely where behavioral economists shine. Far from replacing them, advanced AI tools amplify a behavioral economist’s impact by automating routine tasks. This frees them to focus on the creative, human-centric aspects of data science—crafting experiments, analyzing motivations, and designing interventions that truly resonate with users.

In that sense, behavioral economists are arguably among the least threatened by AI-driven automation. Their expertise in human decision-making, coupled with data fluency, becomes even more valuable as GenAI scales the operational side of data science. Meanwhile, GenAI can supercharge behavioral interventions by enabling rapid prototyping of personalized nudges and real-time experimentation. It’s a synergistic relationship: AI provides powerful tools, while behavioral economists supply the theoretical and ethical grounding to ensure those tools serve genuine human needs rather than just automated optimization.

Finally, what advice would you give a young Cypriot who is fascinated by human decision-making but also drawn to the island’s booming tech sector and the professional opportunities that lie there? Are these two interests compatible—or even complementary?

The tech sector is indeed booming in Cyprus, and that should be great news to behavioral economists. Behavioral science and tech are not just compatible—they often amplify one another when applied thoughtfully. Data science and coding skills enable you to process and analyze large datasets. Behavioral economics provides insights into human decision-making and motivation. Together, these create powerful, human-centric solutions in product development, UX design, and policy-making.

Finally, a parting thought for new behavioral economists - don’t wait for a company to see the value of behavioral economics. Show it to them. Craft a proposal and email it to the company’s HR, or call and ask to set up a meeting with their tech team. It’s hard for a company to ignore really great ideas.

You can watch the entire discussion with Dr. Aristidou on YouTube by following this link: https://www.youtube.com/watch?v=mwu1SHd6l7o

Or listen to it on Spotify by going here:

https://open.spotify.com/episode/28M4LDMuLPVHhx65RreAar?si=gl-miEEETaS22D1aaM_Bug

*Philippos Louis, coordinator of the Master (MSc) in Behavioral Economics at the University of Cyprus