Netflix Logo

Netflix

Data Scientist 4- Messaging Data Science & Engineering

Reposted 29 Days Ago
Remote
Hiring Remotely in USA
280K-421K Annually
Mid level
Remote
Hiring Remotely in USA
280K-421K Annually
Mid level
Design measurement frameworks and advanced causal inference solutions for marketplace allocation and recommendation systems. Partner with Product, Engineering, and business stakeholders to translate needs into scalable data science tools, run experiments, quantify impact, and drive implementation for Netflix discovery surfaces.
The summary above was generated by AI

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.

Netflix New York, New York, USA Office

245 W 17th St, New York, NY, United States, 10011

Similar Jobs

20 Minutes Ago
Easy Apply
Remote or Hybrid
United States
Easy Apply
Junior
Junior
Legal Tech • Software • Generative AI
Manage SaaS renewal operations, including auto-renewals, forecasting, contract audits, renewal briefs, account research, and commercial preparation. Partner with customer success, sales, finance, and deal desk teams to improve retention and renewal execution. Gradually assume ownership of scaled and mid-market renewals, support enterprise strategies, and help build scalable renewal playbooks, tooling, and documentation. Use AI tools for research, proposals, forecasting, and customer outreach.
Top Skills: AICatalystGainsightHubspotSalesforceVitally
20 Minutes Ago
Easy Apply
Remote or Hybrid
United States
Easy Apply
131K-260K Annually
Senior level
131K-260K Annually
Senior level
Artificial Intelligence • Cloud • Computer Vision • Hardware • Internet of Things • Software
Own commercial navigation features end to end across mobile, backend, and web surfaces. Build reliable, customer-facing navigation experiences for commercial fleets despite poor connectivity, dynamic schedules, and changing routes. Define product priorities and success metrics, ship maintainable and tested code, improve observability, and collaborate with product, design, Maps, Telematics, and adjacent engineering teams. The role requires strong customer focus, technical depth, and the ability to make practical tradeoffs in ambiguous problem spaces.
Top Skills: Geospatial And Mapping TechnologiesInternet Of Things (Iot)KotlinReact NativeSwift
42 Minutes Ago
In-Office or Remote
14 Locations
100K-120K Annually
Junior
100K-120K Annually
Junior
Productivity • Software • App development • Automation
Creates accurate, practical technical content for developers, including tutorials, how-to guides, code-led articles, and integration resources. Translates product capabilities and technical concepts into clear content, improves discoverability across search and AI channels, and collaborates with engineering, product, documentation, and subject-matter experts to verify technical accuracy. The role also supports broader marketing deliverables and adapts content for different audiences and buyer-journey stages.
Top Skills: APIsGitOcrPdf SdksSdks

What you need to know about the NYC Tech Scene

As the undisputed financial capital of the world, New York City is an epicenter of startup funding activity. The city has a thriving fintech scene and is a major player in verticals ranging from AI to biotech, cybersecurity and digital media. It also has universities like NYU, Columbia and Cornell Tech attracting students and researchers from across the globe, providing the ecosystem with a constant influx of world-class talent. And its East Coast location and three international airports make it a perfect spot for European companies establishing a foothold in the United States.

Key Facts About NYC Tech

  • Number of Tech Workers: 549,200; 6% of overall workforce (2024 CompTIA survey)
  • Major Tech Employers: Capgemini, Bloomberg, IBM, Spotify
  • Key Industries: Artificial intelligence, Fintech
  • Funding Landscape: $25.5 billion in venture capital funding in 2024 (Pitchbook)
  • Notable Investors: Greycroft, Thrive Capital, Union Square Ventures, FirstMark Capital, Tiger Global Management, Tribeca Venture Partners, Insight Partners, Two Sigma Ventures
  • Research Centers and Universities: Columbia University, New York University, Fordham University, CUNY, AI Now Institute, Flatiron Institute, C.N. Yang Institute for Theoretical Physics, NASA Space Radiation Laboratory

Sign up now Access later

Create Free Account

Please log in or sign up to report this job.

Create Free Account