Lead Data Scientist

This is a fully remote position, open to applicants in California, +3 more states.

📋 Description

• Conduct causal inference analyses, including difference-in-differences, matching, and uplift modeling, under the supervision of the Senior Director.

• Analyze subscriber behaviors that enhance retention and long-term value while addressing known biases within streaming data.

• Map the subscriber journey to assess the effects of lifecycle, product, pricing, and promotional strategies.

• Design, implement, and evaluate A/B tests for acquisition, onboarding, engagement, and win-back initiatives.

• Perform power analysis, monitor experiments, and present findings.

• Develop and sustain reporting and models that translate journey optimization into Average Revenue Per User (ARPU), survival, and Lifetime Value (LTV) metrics.

• Manage SQL/Python data extraction, cleaning, and analysis processes for causal and LTV modeling.

• Create clear presentations and summaries of insights for stakeholders.

• Collaborate with Data Engineering and Product Analytics to ensure data quality and address issues in experimentation and behavioral data pipelines.

• Stay updated on causal inference and experimentation best practices while promoting effective methodologies across the team.

• Mentor junior analysts in SQL, statistical methods, and analytical best practices.

⛳️ Requirements

• A Bachelor's degree in a quantitative discipline (Statistics, Economics, Data Science, Computer Science, Operations Research, or a related field).

• Over 5 years of experience in data science or analytics.

• Practical experience with causal inference or experimentation techniques, including A/B testing, difference-in-differences, or propensity score matching.

• Proficiency in designing or analyzing A/B tests.

• Awareness of experimentation challenges, such as novelty effects, selection bias, and sample ratio mismatch.

• Strong SQL skills.

• Expertise in Python or R for statistical analysis.

• Experience in developing or working with LTV, survival, or churn-related metrics.

• Ability to convey analytical findings clearly to non-technical stakeholders.

• Background in subscription or direct-to-consumer (DTC) streaming, media, or other subscription-based businesses is a plus.

• Familiarity with mapping the subscriber/customer journey is an added benefit.

• Exposure to advanced causal techniques is an additional advantage.

• Knowledge of cloud data warehousing/BI tools such as BigQuery, Databricks, Looker, or Tableau is also advantageous.

🏝️ Benefits

• Medical insurance.

• Dental insurance.

• Vision insurance.

• 401(k) plan.

• Life insurance coverage.

• Disability benefits.

• Tuition assistance program.

• Paid time off (PTO).

• Bonus eligibility.

• Competitive salary alongside comprehensive benefits packages.

• Opportunities for both on-site and virtual engagement events.

• Chances to forge meaningful connections and cultivate a vibrant community.