Lead Data Scientist

Lead Data ScientistWeAreParamount on a mission to unleash the power of content… you in? We've got the brands, we've got the stars, we've got the power to achieve our mission to entertain the planet – now all we're missing is… YOU! Becoming a part of Paramount means joining a team of passionate people who not only recognize the power of content but also enjoy a touch of fun and uniqueness. Together, we co-create moments that matter – both for our audiences and our employees – and aim to leave a positive mark on culture.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.Help map the subscriber journey to pinpoint where lifecycle, product, pricing, and promo levers have the most impact.Help design, set up, and analyze A/B tests across the subscriber journey (acquisition, onboarding, engagement, win-back), including power analysis, monitoring, and read-outs.Build and maintain reporting and models that turn journey optimization into ARPU, survival, and LTV metrics for stakeholders.Own the SQL/Python data pulls, cleaning, and analysis pipelines behind the team's causal and LTV modeling.Prepare clear, well-organized presentations and summaries of your findings for stakeholders.Partner with Data Engineering and Product Analytics to check data quality and fix issues in our experimentation and behavioral data pipelines.Stay current on causal inference and experimentation best practices and help promote sound methods across the team.Mentor junior analysts on SQL, statistical methods, and analytical best practices as the team grows.Basic Qualifications: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.Additional Qualifications:Experience in subscription/DTC streaming, media, or another subscription business (e.g., SaaS, telecom).Familiarity with subscriber/customer journey mapping.Exposure to advanced causal techniques (e.g., instrumental variables, double machine learning, causal forests).Familiarity with cloud data warehousing/BI tools (e.g., BigQuery, Databricks, Looker, Tableau).Paramount Skydance Corporation (NASDAQ: PSKY) is a leading global media and entertainment company that creates premium content and experiences for audiences worldwide. Driven by iconic studios, networks and streaming services, Paramount's portfolio of consumer brands includes CBS, Showtime Networks, Paramount Pictures, Nickelodeon, MTV, Comedy Central, BET, Paramount+, and Pluto TV, among others. Paramount delivers the largest share of the U.S. television audience and boasts one of the industry's most important and extensive libraries of TV and film titles. In addition to offering innovative streaming services and digital video products, the company provides powerful capabilities in production, distribution and advertising solutions.Hiring Salary Range: $139,000.00 - 200,000.00. The hiring salary range for this position applies to New York City, California, Colorado, Washington state, and most other geographies. Starting pay for the successful applicant depends on a variety of job-related factors, including but not limited to geographic location, market demands, experience, training, and education. The benefits available for this position include medical, dental, vision, 401(k) plan, life insurance coverage, disability benefits, tuition assistance program and PTO or, if applicable, as otherwise dictated by the appropriate Collective Bargaining Agreement. This position is bonus eligible.Paramount is an equal opportunity employer (EOE) including disability/vet. At Paramount, the spirit of inclusion feeds into everything that we do, on-screen and off. From the programming and movies we create to employee benefits/programs and social impact outreach initiatives, we believe that opportunity, access, resources and rewards should be available to and for the benefit of all. Paramount is proud to be an equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ethnicity, ancestry, religion, creed, sex, national origin, sexual orientation, age, citizenship status, marital status, disability, gender identity, gender expression, and Veteran status. If you are a qualified individual with a disability or a disabled veteran, you may request a reasonable accommodation if you are unable or limited in your ability to use or access as a result of your disability. You can request reasonable accommodations by calling View phone number on click.appcast.io or by sending an email to View email address on click.appcast.io. Only messages left for this purpose will be returned.