This is a high-leverage role: rather than supporting a single team's experiments, you will set the standards, tooling, and product direction that every data scientist running an experiment at Netflix depends on.
Responsibilities
XP Strategy & Influence: Help set the strategy for the Experimentation Platform, including UI design, and user flows. Define how data scientists contribute metrics, reports, and templates to the platform so they have high leverage when setting standards for experiments in their own space.
Trust & Methodology: Verify that XP allocates, logs, and processes data using valid, trustworthy causal inference methods, and demonstrate that trustworthiness to partner teams - turning verification into automated, recurring, monitored practice rather than one-off checks.
Cross-Functional Collaboration: Act as a strategic thought partner for data science and engineering stakeholders across Netflix. Bridge the gap between data science requirements and platform engineering implementation, representing the DS organization's needs directly to engineering leadership.
Platform Leadership: Influence and evolve how Netflix performs experimentation at scale - setting standards for inference practices (e.g. peeking, covariate adjustment, any-time valid methods, metric definitions, allocation mechanisms) and driving adoption of those practices across data science teams that range from long-tenured streaming teams to newer verticals like Ads.
Lead the consolidation of fragmented, bespoke experimentation systems into a coherent, maintainable platform by building the tools and processes that make best practice the path of least resistance.
Mentor and raise the bar for other team members working on or with the platform, and represent XP's point of view in company-wide discussions on experimentation methodology.
Qualifications
Advanced degree (PhD or Masters) in Computer Science, Statistics, Economics, Applied Mathematics, or a related quantitative field.
8+ years of experience with statistics / causal inference in an experimentation context, including designing experiments at scale and diagnosing them when they break.
Demonstrated track record of setting standards or building tools that were adopted across multiple teams or an entire organization - not just applying judgment project by project.
Deep, practical knowledge of experimentation pitfalls and how to guard against them at a program level: sample ratio mismatches, winner's curse and regression to the mean, false discovery rate across a portfolio of tests, peeking, covariate adjustment, and allocation-vs-analysis-unit mismatches.
Experience translating ambiguous data science pain points into a sequenced product roadmap, including judgment on what a platform should build in, expose as a self-serve primitive, or explicitly not support.
5+ years experience with data science languages, ideally including Python and SQL; comfort partnering closely with engineers on API/schema/system design.
Excellent cross-functional communication skills, with a demonstrated ability to influence skeptical stakeholders - both highly technical (data scientists, engineers) and non-technical business partners to adopt new methods or standards.
Curiosity to learn new statistics, methods, and optimization techniques, and the judgment to know when established methods are the better choice.
Curious to learn more about our experimentation culture at Netflix? Read up on and browse the Netflix Research page.
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 $491,000.00 - $775,000.00. 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.
Job is open for no less than 7 days and will be removed when the position is filled.
