Data Scientist

Must Have:

Python Machine Learning data science AWS Statistical Modeling Semantic Search Vector DB GenAI SQL

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 Disneys 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 7 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 5 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.