Machine Learning Scientist 4 - Subscription Forecasting

Posted 8 Hours Ago
Be an Early Applicant
Hiring Remotely in USA
Remote
300K-537K Annually
Mid level
News + Entertainment
The Role
As a Machine Learning Scientist, you will build and enhance forecasting models for Netflix's subscription business, collaborate with various teams, and improve statistical forecasting methods while considering external market signals.
Summary Generated by Built In

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.

The Team

Netflix's ability to invest in the content that entertains hundreds of millions of members - billions of dollars each year across film, series, games, and live experiences - depends on getting subscription pricing right and having a clear view of where the business is headed.

The Subscription Revenue DSE team brings measurement and modeling to both challenges. We are a small, focused group of data practitioners who work across pricing research and business forecasting. This role will focus on the forecasting work, where we partner with Finance & Strategy, Content, and Revenue Analytics teams to build the models that project Netflix's subscriber growth, engagement, and revenue across global markets over multi-year horizons. Our forecasts serve as a foundation for long-range planning across the company.

The Role

You will work closely with senior researchers and the team's existing data science foundation to improve the models that forecast Netflix's subscription trajectory and the expected impact of pricing decisions.

The core challenge: subscription markets are noisy, global, and deeply interconnected. Understanding how the business will develop - and how pricing actions will shift that trajectory - across geographies, plan tiers, and time horizons requires strong models and honest judgment about what the data can and can't tell you.

What You Will Do
  • Build and productionize forecasting models that capture the overall trajectory of Netflix's subscription business alongside the expected impact of pricing actions on member base, ARPU, and revenue across global markets

  • Build on the team's existing scenario modeling and simulation tools to quantify how pricing actions and broader market dynamics are expected to affect subscription metrics - giving decision-makers a way to stress-test assumptions before a pricing move happens

  • Contribute to and advance the team's forecasting pipeline - model development, backtesting, deployment, and monitoring - and lift the accuracy and reliability of existing forecasts

  • Partner with Finance & Strategy and Product leadership to translate forecast outputs - including their uncertainty - into concrete business recommendations

About You
  • Solid grasp of subscription business dynamics - how acquisition, ARPU, and churn interact, and how pricing decisions move these metrics

  • Strong expertise across forecasting methods - such as time series, and regression-based approaches - and the trade-offs between accuracy, interpretability, and stability

  • Comfortable building production forecasting systems: backtesting, monitoring, catching drift, and retraining when the data changes

  • You incorporate macro and external signals (economic conditions, FX dynamics, competitive moves) into your models alongside internal data

  • Proficient in Python and SQL, with hands-on experience with ML and statistical libraries (e.g., statsmodels, PyTorch)

  • Advanced degree (MS or PhD) in statistics, economics, computer science, or a related quantitative field, or equivalent applied experience


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 $300,000.00 - $537,000.00. 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.

Top Skills

Python
PyTorch
SQL
Statsmodels
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The Company
HQ: Los Gatos, CA
13,212 Employees
Year Founded: 1997

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.

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