Lead Data Scientist
- Compensation
- Not disclosed
- Location
- Not listed
- Work setup
- Not specified
- Seniority
- Lead
- Employment
- Not specified
- Experience
- 5+ years
- Category
- Data science
- Posted
Skills
Must have
- Bachelor's degree in a quantitative field (Statistics, Economics, Data Science, Computer Science, Operations Research, or related).
- 5+ years in data science/analytics, with hands-on use of causal inference or experimentation methods (e.g., A/B testing, diff-in-diff, propensity score matching) — not just predictive modeling.
- Experience designing or analyzing A/B tests, including an understanding of common pitfalls (novelty effects, selection bias, sample ratio mismatch).
- Solid SQL skills and proficiency in Python or R for statistical analysis.
- Experience working with or building LTV, survival, or churn-related metrics.
- Great communication skills, with the ability to turn analytical results into clear takeaways for non-technical stakeholders.
Full description
Storytelling is, and will always be, the heart of what we do at Skydance.
Our vision is to build a thriving entertainment ecosystem where stories and worlds are imagined, brought to life and experienced. We create for every age and audience, anchored by the strength of our content and experiences and the depth of our connection with fans. We are creator-first, audience-focused, tech-forward, globally scaled.
Here, you’ll work with talented teams that move fast, think boldly and collaborate with purpose to deliver results. We aim high, champion the best ideas and win together, earning the trust of our employees, creators, partners and audiences every day.
If you’re energized by the opportunity to help build the next-generation global media and entertainment company powered by creativity and technology, we’d be thrilled to welcome you aboard. LET’S GO!
Overview:
We are the Global Content and Lifecycle Analytics team, part of the Paramount Streaming, Data & Insights Group (DIG)! DIG is a key connector across the Paramount Streaming verticals. Our group is made up of subject matter experts who prototype, build, and scale data infrastructure and products. We also assess, aggregate, and analyze data, and we shape both qualitative and quantitative stories and insights. In short, we give our stakeholders decision support, clear performance views, and recommendations that help the business grow!
The User Lifecycle Analytics team works closely with Lifecycle Marketing, Product, Finance, and DTC Executives to drive subscriber growth and retention.
The Lead Data Scientist reports to the Senior Director of Data Science. You'll support a wide range of projects, partnering with the Lifecycle Marketing and Product teams, DTC executives, and Finance. This role calls for a solid analytical foundation, real curiosity about subscriber behavior, and the skill to run careful analysis that feeds straight into strategy!
The ideal candidate is detail-oriented, communicates clearly, and has hands-on experience (or eagerness to grow) in causal inference and experimentation.
This role supports two core business questions:
- What drives long-term subscriber health, and how do we use our levers (lifecycle, product, pricing, promotions) to grow it?
- How do our optimization efforts across content and the subscriber journey affect the bottom line?
Responsibilities:
- Run causal inference analyses (e.g., diff-in-diff, matching, uplift modeling) under the Sr. Director's guidance. You'll find which subscriber behaviors truly drive retention and long-term value, while correcting for known biases in streaming data.
- Help map the subscriber journey to pinpoint where lifecycle, product, pricing, and promo levers have the most impact.