Lead Data Scientist

Paramount

Lead Data Scientist applying causal inference and experimentation to Paramount’s streaming subscriber growth and retention. Building LTV models and analytics for lifecycle, product, pricing, and promotion decisions.

Posted 9/1/2026full-timeRemote • California, Colorado, New York, Washington • 🇺🇸 United StatesSenior💰 $139,000 - $200,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in causal inference analyses and A/B testing methodologies, with a strong ability to translate complex data insights into actionable metrics such as ARPU and LTV. Proficient in SQL and Python for data analysis, with a focus on optimizing subscriber journeys in subscription-based businesses.

Highest-signal resume keywords

Causal Inference AnalysisA/B Testing DesignSQL ProficiencyPython for Statistical AnalysisSubscriber Journey Mapping

ATS Keywords

Tailor your resume

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills

Causal InferenceDiff-In-Diff AnalysisMatching TechniquesUplift ModelingStatistical AnalysisLTV MetricsSurvival MetricsChurn AnalysisExperiment MonitoringPower Analysis

Soft Skills

Clear CommunicationMentoring

Tools & Technologies

BigQueryDatabricksLookerTableau

Industry Keywords

Subscription BusinessDTC StreamingMedia AnalyticsBehavioral Data Pipeline

Tech Stack

Tools & technologies

BigQueryCloudPythonSQLTableau

About the role

Key responsibilities & impact

Run causal inference analyses, including diff-in-diff, matching, and uplift modeling, under the Senior Director's guidance
Identify subscriber behaviors that drive retention and long-term value while correcting for known biases in streaming data
Map the subscriber journey to identify the impact of lifecycle, product, pricing, and promotional levers
Design, set up, and analyze A/B tests across acquisition, onboarding, engagement, and win-back
Conduct power analysis, experiment monitoring, and read-outs
Build and maintain reporting and models translating journey optimization into ARPU, survival, and LTV metrics
Own SQL/Python data pulls, cleaning, and analysis pipelines for causal and LTV modeling
Prepare clear presentations and summaries of findings for stakeholders
Partner with Data Engineering and Product Analytics to validate data quality and resolve experimentation and behavioral data pipeline issues
Stay current on causal inference and experimentation best practices and promote sound methods across the team
Mentor junior analysts on SQL, statistical methods, and analytical best practices

Requirements

What you’ll need

Bachelor's degree in a quantitative field (Statistics, Economics, Data Science, Computer Science, Operations Research, or related)
5+ years in data science/analytics
Hands-on use of causal inference or experimentation methods, such as A/B testing, diff-in-diff, or propensity score matching
Experience designing or analyzing A/B tests
Understanding of experimentation pitfalls, including novelty effects, selection bias, and sample ratio mismatch
Solid SQL skills
Proficiency in Python or R for statistical analysis
Experience working with or building LTV, survival, or churn-related metrics
Ability to communicate analytical results clearly to non-technical stakeholders
Experience in subscription/DTC streaming, media, or another subscription business is an additional qualification
Familiarity with subscriber/customer journey mapping is an additional qualification
Exposure to advanced causal techniques is an additional qualification
Familiarity with cloud data warehousing/BI tools such as BigQuery, Databricks, Looker, or Tableau is an additional qualification

Benefits

Comp & perks

Medical insurance
Dental insurance
Vision insurance
401(k) plan
Life insurance coverage
Disability benefits
Tuition assistance program
Paid time off (PTO)
Bonus eligibility
Attractive compensation and comprehensive benefits packages
Opportunities for on-site and virtual engagement events
Opportunities to make meaningful connections and build a vibrant community