Overview:We are the Global Content and Lifecycle Analytics team, part of the Paramount Streaming, Data & Insights Group (DIG) team. DIG is a key connector among the Paramount Streaming verticals. The group consists of subject matter experts that prototype, build, and scale data infrastructure and products; assess, aggregate, and analyze data; and shape qualitative and quantitative based narratives and insights, providing stakeholders with decision support, performance clarity and business driving recommendations.
The User Lifecycle Analytics team works closely with Lifecycle Marketing, Product, Finance, and DTC Executives to drive subscriber growth and retention.
The Senior Director will report into the VP of User Lifecycle Analytics, and will support a wide range of initiatives, partnering with the Lifecycle Marketing and Product teams, DTC executives and Finance. This role requires the ability to translate complex data into clear, actionable insights and strategic recommendations.
The ideal candidate will possess strong communication skills, an inquisitive nature, attention to detail, and a passion for media, ideally with experience in analyzing user journeys and advanced causal inference frameworks.
This role owns two core business questions:
- What drives long-term subscriber health, and how do we use our levers (lifecycle, product, pricing, promotions) to encourage it?
- How are optimization efforts across content and the subscriber journey impacting the bottom line?
Responsibilities:- Design and lead causal inference frameworks (quasi-experimental methods, uplift modeling, instrumental variables, matching, diff-in-diff). Find what truly drives retention and value.
- Work with Lifecycle Marketing and Product to turn causal findings into clear levers. These span content, onboarding, pricing, and promos to improve subscriber health.
- Own how we link content and journey optimization to outcomes like ARPU, survival, and LTV.
- Design, launch, and analyze A/B tests across the subscriber journey (acquisition, onboarding, involvement, win-back). Use sound design. Deliver clear results.
- Build and keep LTV and survival models with the causal drivers above. Finance and DTC teams can then use them.
- Lead subscriber journey mapping. Find where levers (lifecycle, product, pricing, promos) drive the most causal impact on retention and monetization.
- Run pricing and promo analyses to shape pricing and promo design. Weigh short-term conversion against long-term value.
- Explain technical findings clearly to non-technical teams, like DTC leaders and Finance.
- Manage, mentor, and grow a team of data scientists and analysts. Set technical standards and review methods.
- Work with Data Engineering and Product Analytics. Keep the data systems for causal analysis (experiment platforms, behavioral and billing data) reliable.
- Share findings with senior leaders to shape the roadmap. Guide where we invest across Marketing, Product, and Finance.
Basic Qualifications:- Bachelor's degree in a quantitative field (Statistics, Economics, Data Science, or Computer Science).
- 10+ years in data science/analytics. This covers hands-on and team-leading work. It spans causal inference methods (diff-in-diff, propensity matching, instrumental variables, uplift modeling, synthetic control).
- Experience designing and analyzing A/B tests and experiments at scale, handling common pitfalls (novelty and network effects, selection bias).
- Built or run LTV, survival, or churn models. Turned them into financial metrics (ARPU, retention curves).
- Strong SQL skills and a stats language (Python or R) for causal modeling.
- A proven track record leading and growing a team of data scientists or analysts.
- A clear communicator who can present complex work to senior leaders and shape decisions.
- Experience working across Marketing, Product, and Finance teams.
Additional Qualifications:- Know pricing awareness/elasticity work. Design smart promos.
- Skilled in subscriber/customer journey mapping.
- Skilled in Bayesian or ML-based causal techniques (e.g., double machine learning, causal forests).
- Familiarity with cloud data warehousing/BI tools (e.g., BigQuery, Databricks, Looker, Tableau).
ADDITIONAL INFORMATION
Hiring Salary Range: $234,000.00 - 300,000.00.
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.
What We Offer:- Attractive compensation and comprehensive benefits packages. Check out our full list of benefits here: https://www.paramount.com/careers/benefits
- Generous paid time off.
- An exciting and fulfilling opportunity to be part of one of Paramount's most dynamic teams.
- Opportunities for both on-site and virtual engagement events.
- Unique opportunities to make meaningful connections and build a vibrant community, both inside and outside the workplace.
- Explore life at Paramount: https://www.paramount.com/careers/life-at-paramount
