{"id":4243752,"url":"https://alion.io/job/paramount-lead-data-scientist","title":"Lead Data Scientist","company":{"id":6984,"name":"Paramount","domain":"paramount.com","url":"https://alion.io/company/paramount","size_band":"51-200","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"SuccessFactors","truth_index":null},"role":"Data Science","role_family":"Data Science","seniority":"lead","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["New York, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":139000,"max":200000,"currency":"USD","period":"year","gross":null,"usd_annual":200000},"salary_estimate":null,"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"A/B Testing","optional":false},{"name":"Databricks","optional":false},{"name":"Google BigQuery","optional":false},{"name":"Looker","optional":false},{"name":"Machine Learning","optional":false},{"name":"Python","optional":false},{"name":"SQL","optional":false},{"name":"Tableau","optional":false}],"status":"live","first_seen_at":"2026-10-29T07:00:00Z","employer_posted_date":"2026-10-29","last_verified_at":"2026-11-13T12:27:52Z","board_verified":true,"closed_at":null,"days_open":15,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":15},"description":"Storytelling is, and will always be, the heart of what we do at Skydance.\nOur 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.\nHere, 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.\nIf 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!\nOverview:\nWe 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!\nThe User Lifecycle Analytics team works closely with Lifecycle Marketing, Product, Finance, and DTC Executives to drive subscriber growth and retention.\nThe 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!\nThe ideal candidate is detail-oriented, communicates clearly, and has hands-on experience (or eagerness to grow) in causal inference and experimentation.\nThis role supports two core business questions:\nWhat drives long-term subscriber health, and how do we use our levers (lifecycle, product, pricing, promotions) to grow it?\nHow do our optimization efforts across content and the subscriber journey affect the bottom line?\nResponsibilities:\nRun 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.\nHelp map the subscriber journey to pinpoint where lifecycle, product, pricing, and promo levers have the most impact.\nHelp design, set up, and analyze A/B tests across the subscriber journey (acquisition, onboarding, engagement, win-back), including power analysis, monitoring, and read-outs.\nBuild and maintain reporting and models that turn journey optimization into ARPU, survival, and LTV metrics for stakeholders.\nOwn the SQL/Python data pulls, cleaning, and analysis pipelines behind the team's causal and LTV modeling.\nPrepare clear, well-organized presentations and summaries of your findings for stakeholders.\nPartner with Data Engineering and Product Analytics to check data quality and fix issues in our experimentation and behavioral data pipelines.\nStay current on causal inference and experimentation best practices and help promote sound methods across the team.\nMentor junior analysts on SQL, statistical methods, and analytical best practices as the team grows.\nBasic Qualifications:\nBachelor's degree in a quantitative field (Statistics, Economics, Data Science, Computer Science, Operations Research, or related).\n5+ 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.\nExperience designing or analyzing A/B tests, including an understanding of common pitfalls (novelty effects, selection bias, sample ratio mismatch).\nSolid SQL skills and proficiency in Python or R for statistical analysis.\nExperience working with or building LTV, survival, or churn-related metrics.\nGreat communication skills, with the ability to turn analytical results into clear takeaways for non-technical stakeholders.\nAdditional Qualifications:\nExperience in subscription/DTC streaming, media, or another subscription business (e.g., SaaS, telecom).\nFamiliarity with subscriber/customer journey mapping.\nExposure to advanced causal techniques (e.g., instrumental variables, double machine learning, causal forests).\nFamiliarity with cloud data warehousing/BI tools (e.g., BigQuery, Databricks, Looker, Tableau).\n\nAbout Skydance\n Skydance is a next-generation global media and entertainment company, comprised of three business segments: Studios, Direct-to-Consumer, and TV Media. Skydance's portfolio unites legendary brands, including Paramount, Warner Bros., HBO and HBO Max, Paramount+, Pluto TV, CBS, CNN, CBS Sports, TNT Sports, Nickelodeon, Cartoon Network, MTV, Food Network, BET, HGTV, and Comedy Central.\nADDITIONAL INFORMATION\nHiring Salary Range: $139,000.00 - 200,000.00.\nIn compliance with local law, we are disclosing compensation, or a range thereof, for roles where legally required. Actual salaries will vary based on a variety of job-related factors, including but not limited to geographic location, external market data, internal equity, skill set, experience, training, education, and/or performance. Base pay is just one component of our total compensation package. Other rewards may include annual bonuses, short- and long-term incentives, and program-specific awards.\nThis position is bonus eligible.\nWhat We Offer:\nAttractive compensation and comprehensive benefits packages. Check out our full list of benefits here.\nGenerous paid time off.\nComplimentary subscriptions to HBO Max, Paramount+, and other Skydance streaming services and digital news products.\nRobust employee engagement opportunities, including access to exclusive screenings and events, speaker series, volunteer activities and more.\nSkydance is an equal opportunity employer (EOE)\nWe embrace the opportunity to build a workforce that reflects a wide array of perspectives, backgrounds and experiences. Being an equal opportunity employer means that we take seriously our responsibility to consider qualified candidates on the basis of merit. In line with the laws of the country or region in which the role is based, this includes consideration without regard to race, color, ethnicity, national origin, citizenship status, religion or belief, sex, gender, gender identity or expression, sexual orientation, age, marital status, pregnancy, parenthood, physical or mental disability, genetic information, military or protected veteran status, union status or any other category protected by applicable law.\nIf you are a qualified individual with a disability, you may request a reasonable accommodation during the job application and/or recruitment process. You can request reasonable accommodations by calling 212.846.5500 or by sending an email to . 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