At Netflix, our mission is to entertain the world. Together, we are writing the next episode - pushing the boundaries of storytelling, global fandom and making the unimaginable a reality. We are a dream team obsessed with the uncomfortable excitement of discovering what happens when you merge creativity, intuition and cutting-edge technology. Come be a part of what’s next.
Interactive Discovery covers the ways members explicitly tell Netflix what they want, rather than waiting to be served a recommendation, and it has two components. The first one is our Search platform, which aims at seamlessly integrating with a member’s entire discovery process, powered by intelligent querying systems. The second one is Member Spaces & Inputs, which aims at enabling a member’s discovery journey from anticipating and planning to watch certain content, to tuning in at the right moment through features such as Continue Watching, My List, and Remind Me.
The Team: Interactive Discovery DSE
The Interactive Discovery Data Science & Engineering team builds the data, analytics, and experimentation strategy across Search and Inputs – from how Search and GenSearch understand and respond to what a member is looking for, to how features like Continue Watching, My List, and Remind Me help members act on their intent throughout their discovery journey. We partner closely with Product, Engineering, Algos, and Consumer Insights to advance the science behind the various product features, and hold ourselves to a high bar because getting it right means members spend less time searching and more time watching something they’ll love.
We are seeking a Data Scientist with a strong background in experimentation and causal inference to lead the day-to-day partnership between Interactive Discovery DSE and our Member Spaces & Inputs product team. You will design rigorous tests, exercise judgment on what counts as sufficient evidence to validate a hypothesis, and build the measurement frameworks that help the broader Interactive Discovery org move faster and with more confidence.
In this role, you will:
- Design and run rigorous A/B tests evaluating Member Spaces & Inputs feature interventions’ impact on user experience
- Exercise causal inference techniques when a clean test isn’t feasible, so the team can still make confident calls in situations where standard experimentation frameworks don’t apply
- Help define and evolve Interactive Discovery’s experimentation standards and measurement framework, developing a shared playbook that lets the broader team run tests with high rigor
- Own the code, data pipelines, and dataset enrichment your analyses depend on, so results are reliable and stakeholders can act on them with confidence
- Translate complex statistical findings into clear, actionable recommendations to influence product decisions and future strategy
- Set the tone for the day-to-day partnership between DSE and Member Spaces & Inputs product team, translating open-ended business needs into well-scoped data projects, sharing a data-driven opinions on roadmap and prioritization
- Build data solutions that could scale as Interactive Discovery innovates and expands into new business verticals (e.g. Live, Games)
To be successful in this role, you have:
- At least 3 years of relevant experience, with demonstrated strength in experimentation and causal inference
- Hands-on experience designing and analyzing experiments, with comfort applying causal inference and measurement techniques beyond vanilla A/B tests
- Exceptional communication skills with technical and non-technical audiences, able to influence your partners using clear actionable insights and recommendations
- Strong thought partnership, able to own direct relationships with stakeholders and build credibility through clarity and judgment
- Ability to translate ambiguous asks into clear data science solutions to influence the business
- Strong SQL and Python skills, including building dashboards and automations that improve team efficiency and surface insights
- Good judgment to balance between addressing stakeholder or test-specific needs and investing in scalable solutions to serve general use cases
- Ability to work independently, drive your own projects end-to-end, and thrive in ambiguous situations
Additionally, an exceptional candidate will have:
- Experience with algorithms as a product
- PhD/Masters degree in Statistics, Economics, Computer Science, Mathematics, or a related quantitative field
- Familiarity with Gen AI productivity tools
Generally, our compensation structure consists solely of an annual salary; we do not have bonuses. You choose each year how much of your compensation you want in salary versus stock options. To determine your personal top of market compensation, we rely on market indicators and consider your specific job family, background, skills, and experience to determine your compensation in the market range. The range for this role is $280,000.00 - $421,000.00. This compensation range will vary based on location.
Netflix provides comprehensive benefits including Health Plans, Mental Health support, a 401(k) Retirement Plan with employer match, Stock Option Program, Disability Programs, Health Savings and Flexible Spending Accounts, Family-forming benefits, and Life and Serious Injury Benefits. We also offer paid leave of absence programs. Full-time hourly employees accrue 35 days annually for paid time off to be used for vacation, holidays, and sick paid time off. Full-time salaried employees are immediately entitled to flexible time off. See more details about our Benefits here.
Netflix is a unique culture and environment. Learn more here.
Inclusion is a Netflix value and we strive to host a meaningful interview experience for all candidates. If you want an accommodation/adjustment for a disability or any other reason during the hiring process, please send a request to your recruiting partner.
We are an equal-opportunity employer and celebrate diversity, recognizing that diversity builds stronger teams. We approach diversity and inclusion seriously and thoughtfully. We do not discriminate on the basis of race, religion, color, ancestry, national origin, caste, sex, sexual orientation, gender, gender identity or expression, age, disability, medical condition, pregnancy, genetic makeup, marital status, or military service.
Job is open for no less than 7 days and will be removed when the position is filled.
Skills Required
- PhD or equivalent in Statistics, Economics, Mathematics, Computer Science, or related quantitative field
- 2-5 years relevant experience focused on marketplace dynamics, experimentation, and causal inference
- Experience building and deploying data science solutions at scale
- Proficiency in Python
- Advanced SQL
- Familiarity with GenAI productivity tools
- Exceptional oral and written communication skills
- Ability to work independently and drive projects end-to-end
- Familiarity with recommendation algorithms, machine learning, and LLMs
- Experience with ads marketplaces or similar allocation systems
- Passion for driving product vision and innovation strategy
- Embodies Netflix values
Netflix Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Netflix and has not been reviewed or approved by Netflix.
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Fair & Transparent Compensation — Compensation is positioned as “personal top of market” with regular recalibration and broad posted ranges for senior roles that signal the philosophy. The cash‑forward structure and clearly described pay‑mix choices help set expectations on how pay is determined.
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Equity Value & Accessibility — Employees can choose the mix of cash versus fully vested 10‑year stock options, with grants structured to be retained even after departure. This employee‑directed design increases accessibility and control over equity participation.
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Healthcare Strength — Health coverage is described as comprehensive across medical, dental, vision, and mental health, with employer funding designed to offset premiums. Additional resources like counseling/coaching and wellness support reinforce breadth in care access.
Netflix Insights
What We Do
Netflix is the world's leading streaming entertainment service with 209 million paid memberships in over 190 countries enjoying TV series, documentaries and feature films across a wide variety of genres and languages. Members can watch as much as they want, anytime, anywhere, on any internet-connected screen. Members can play, pause and resume watching, all without commercials or commitments.








