Senior Director, Data Science

This is a fully remote position, open to applicants in New York.

📋 Description

• Develop and oversee causal inference frameworks to determine the factors influencing retention and subscriber value.

• Collaborate with Lifecycle Marketing and Product teams to convert causal insights into practical strategies across content, onboarding, pricing, and promotions.

• Connect content and subscriber journey enhancements to outcomes related to ARPU, survival, and LTV.

• Create, implement, and evaluate A/B tests throughout acquisition, onboarding, engagement, and win-back processes.

• Construct and sustain LTV and survival models for Finance and DTC groups.

• Guide subscriber journey mapping efforts to pinpoint causal effects on retention and monetization.

• Perform pricing and promotional analysis, weighing immediate conversion against long-term value.

• Articulate technical insights to non-technical teams in DTC and Finance.

• Oversee, mentor, and develop data scientists and analysts; establish technical benchmarks and evaluate methodologies.

• Work with Data Engineering and Product Analytics to ensure dependable systems for experiments, behavioral data, and billing information.

• Present findings to senior leadership to influence strategic roadmaps and investment choices across Marketing, Product, and Finance.

• Report directly to the VP of User Lifecycle Analytics.

⛳️ Requirements

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

• Over 10 years of experience in data science/analytics, featuring both hands-on and leadership roles.

• Familiarity with causal inference techniques such as diff-in-diff, propensity score matching, instrumental variables, uplift modeling, and synthetic control.

• Proven experience in designing and analyzing A/B tests and large-scale experiments.

• Capability to address novelty, network effects, and selection bias in experimental contexts.

• Experience in creating or managing LTV, survival, or churn models.

• Proficiency in translating model outputs into financial metrics like ARPU and retention curves.

• Strong skills in SQL.

• Competence in Python or R for causal modeling tasks.

• A demonstrated history of leading and developing a team of data scientists or analysts.

• Ability to convey complex work to senior leadership and influence decision-making processes.

• Experience collaborating across Marketing, Product, and Finance departments.

• Knowledge in pricing awareness/elasticity studies and effective promotional design.

• Skills in mapping subscriber/customer journeys.

• Experience with Bayesian or machine learning-based causal methods, including double machine learning and causal forests.

• Familiarity with cloud data warehousing and BI tools like BigQuery, Databricks, Looker, or Tableau.

🏝️ 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 and comprehensive benefits packages.

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

• Opportunities to forge meaningful connections and cultivate a dynamic community.

• Commitment to equal employment opportunity and reasonable accommodation support.