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. Messaging is Netflix's most personal, 1:1 touchpoint with our members across off-platform channels such as email and push notifications, as well as in-product channels like interstitials. The scope of Messaging spans across many use cases: promoting catalog discovery, supporting commerce and member lifecycle moments, driving engagement, deepening brand affinity, and handling business-critical communications.

The Team: Messaging DSE As part of the Messaging Data Science & Engineering team, you will build the data, analytics, and experimentation systems behind who gets which message, when, through which channel, and whether it is worth sending. Doing this well means millions of members discover something they love or need, at exactly the right moment. We are seeking a Data Scientist with a strong background in experimentation and causal inference to lead the day-to-day partnership between Messaging DSE and our Consumer Messaging Program team (i.e

our team of CRM experts). You will collaborate closely with CMP and other cross-functional colleagues such as Product, Algos, and Engineering to design rigorous tests, exercise judgment on what counts as sufficient evidence to validate a hypothesis, and build the measurement frameworks that help the broader Messaging org move faster and with more confidence. In this role, you will: Design and run rigorous A/B tests evaluating Messaging strategies (including channel, timing, content, and targeting) with a sharp eye for statistical validity and business relevance 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 Messaging'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 Automate recurring analysis work such as test reads, experiment dashboards, and messaging campaign health checks, turning one-off requests into self-serve tools and repeatable workflows for the team Set the tone for the day-to-day partnership between Messaging DSE and CMP, translating open-ended business asks into well-scoped projects, and bringing data-grounded recommendations to inform future strategies Build data solutions that could scale as Messaging innovates and expands into new business verticals (e.g

Live, Games) or channels 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 CRM, messaging/lifecycle marketing, or campaign analytics 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.