Data Scientist

Title: Data Scientist

location: NYC, NY (Hybrid)

Duration: Full Time

Technical Responsibilities:

● Design and Execute Experiments: Lead end-to-end A/B testing initiatives and Geo Experiments, from hypothesis formation and experimental design to statistical analysis and business recommendations

● Advanced Statistical & Causal Inference: Apply deep knowledge of experimental design, regression, classification, causal inference (difference-in-differences, propensity scores, instrumental variables), and ensure proper assumptions.

● Build Scalable Solutions: Develop experimentation and causal inference tools and frameworks that can scale across Disney's businesses

● Deliver Strategic Insights: Partner with stakeholders to identify optimization opportunities and translate complex analytical findings into clear business recommendations

● Influence Executive Decisions: Present findings and recommendations to senior leadership, effectively communicating statistical concepts to non-technical stakeholders

Basic Qualifications

● Bachelors in Statistics, Economics, Computer Science, Engineering, Mathematics, Physics, or a related field 10+ years of experience with an emphasis on experimentation or causal inference.

● Strong background in statistical modeling: regression, classification, time series forecasting, causal inference, and other techniques.

● Robust knowledge of causal inference approaches such as propensity scores, synthetic controls, difference-in-differences, doubly robust methods, meta learners, and uplift modeling.

● Expertise in A/B test design, execution, statistical modeling, and sophisticated causal inference techniques.

● Proficient in conducting sample size calculations, power analysis, and minimum detectable effect estimation.

● Experience managing multiple testing scenarios and controlling false discovery rates.

● Ability to deploy both Bayesian and frequentist statistical approaches.

● Deep understanding of assumptions required for causal inferences, including the foundational statistical concepts that underpin the approaches.

● Proven ability to manage end-to-end experimentation and causal inference analyses, from initial requirements to impactful outcomes

● Advanced skills in Python and/or R—including development of statistical analysis packages, and use of ML frameworks (e.g., scikit-learn, LGBM).

● Strong communication skills for translating complex data into actionable narratives and presenting confidently to technical and non-technical audiences, including senior executives.

Preferred Qualifications

● MS in computer science, statistics, math or a related quantitative field 10+ years of relevant experience OR PhD + 3 years of relevant experience with an emphasis on experimentation or causal inference.

● Experience with ETL and data engineering: data extraction, transformation, integration, and quality controls for analytics at scale.

● Skilled in production deployment and monitoring of data science solutions, including CI/CD pipelines, automated reporting, and ongoing experiment/model monitoring.

● Familiarity with data platforms and applications such as Databricks, Jupyter, Snowflake, and Github.

● Strong strategic business insight, preferably in subscription-based business models, with ability to apply experimentation and analytics to market trends and consumer insights.

● Proven track record of leadership and stakeholder/project management, including influencing cross-functional teams and delivering high-impact outcomes.

● Adept at adapting quickly to shifting priorities in a fast-moving environment while maintaining quality.

● Drive and maintain a culture of quality, innovation and experimentation.

● Demonstrated experience mentoring colleagues on best practices and technical concepts for building large scale solutions.