Netflix is one of the world's leading entertainment services, with over 300 million paid memberships in over 190 countries enjoying TV series, films and games across a wide variety of genres and languages. Members can play, pause and resume watching as much as they want, anytime, anywhere, and can change their plans at any time.
Our Content business is responsible for weighing trade-offs between budget, schedules, and quality across the movies and shows we produce all around the world. The Media Science DSE team uses data to help the business navigate those decisions with clarity. Our metric frameworks and analysis directly shape how we enable creative teams to produce the best movies and shows for our members.
EMEA is a growing hub within our broader Data & Insights org, and we are looking for a stunning Senior Data Scientist based in Amsterdam to join our growing Studio Production DSE team. In this role, you will partner with Product Management and cross-functional product teams, Finance & Strategy, and Content Operations & Innovation leadership to scale and innovate content creation workflows. Through thoughtful metric research and causal inference modeling, you will have the opportunity to directly influence decision-making around how we produce and innovate on global content production - helping Creatives bring their best vision to life on screen.
As a Senior Data Scientist in this space, you will:Be the second Applied Inference Data Scientist in Media Science Data Science & Engineering, helping shape how the discipline shows up and drives impact in Studio Production
Be a strategic thought partner for Content & Business Product PMs, Content Operations & Innovation leaders and teams, Finance & Strategy, and AI Innovation & Strategy DSE – scoping ambiguous, greenfield questions and proposing data science approaches where no playbook exists
Identify metric research and causal inference opportunities to assess the impact of media innovation efforts and improve the efficiency and effectiveness of media creation
Help Studio navigate cost, time, and quality trade-offs by delivering research that connects production decisions to member and business outcomes
Own your research agenda end to end - from design and execution on causal analysis through to interpretation and dissemination
Present your research and findings clearly to both technical and non-technical partners, translating complex analysis into decisions leadership can act on
Build and maintain strong partnerships with a variety of business and product stakeholders, working directly with them to introduce and influence data-informed ways of working
Collaborate with exceptional Data Scientists and Analytics Engineers in-region and globally to explore our operational data and uncover insights that help creative teams produce even better shows and movies for our members
Serve as a regional expert on Studio Data Science & Engineering, helping educate and connect regional offices to existing research and data solutions from across the team
Advanced degree in Statistics, Mathematics, Physics, Economics, or related quantitative field
5+ years of relevant experience with a variety of causal inference methods, including quasi-experimental designs and managing complexities around smaller sample sizes
Strong statistical knowledge and intuition, utilized in observational causal analysis and applied machine learning settings, with demonstrated business impact
An expert in SQL and Python
Proven track record wrangling data, performing exploratory data analysis, designing metrics and tests, building causal inference solutions, and articulating data stories to deliver meaningful business impact
Strong verbal and written communicator who can develop and deepen effective relationships with a wide variety of stakeholders and communicate technical concepts clearly and concisely to less technical audiences
A self-starter with a learning mindset who is exceptionally curious – eagerly diving into new spaces and bringing informed ideas to the table
Comfortable operating in ambiguity and a fast-paced environment; able to take ownership and thrive with minimal oversight and process
Thrilled about innovating in the Content Production domain via novel experimental techniques and comfortable taking (smart) risks in your work
Extensive experience within the EMEA region, adept at working across different cultures on a globally-distributed team, collaborating with fellow team members and partners to ideate on and deliver impactful research
Netflix culture resonates with you
Plus: Experience creating data products and dashboards such as Tableau
Plus: Designing and analyzing A/B tests
You will have the opportunity to impact the business in a meaningful way, working alongside smart people who love to solve hard problems, and who not only expect but also foster high performance. You will have the freedom to innovate, solve interesting problems, and influence decision-making in a fast-paced, exciting environment. You can learn more about our culture at jobs.netflix.com/culture.
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.
Skills Required
- Advanced degree in Statistics, Mathematics, Physics, Economics, or a related quantitative field
- 5+ years of relevant experience using causal inference methods, including quasi-experimental designs and smaller-sample analysis
- Strong statistical knowledge and intuition applied to observational causal analysis and machine learning
- Expert proficiency in SQL and Python
- Experience wrangling data and performing exploratory data analysis
- Experience designing metrics and tests
- Experience building causal inference solutions with demonstrated business impact
- Ability to communicate technical concepts clearly to technical and non-technical stakeholders
- Strong verbal and written communication skills and stakeholder relationship-building ability
- Ability to operate independently in ambiguity and fast-paced environments
- Experience working across cultures in the EMEA region on globally distributed teams
- Experience creating data products and dashboards such as Tableau
- Experience designing and analyzing A/B tests
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.








