Lead Data Scientist

Role Location: 

This is an on-site role requiring 4 days in-person at designated office location.

Disney Entertainment & ESPN Technology

On any given day at Disney Entertainment & ESPN Technology, we’re reimagining ways to create magical viewing experiences for the world’s most beloved stories while also transforming Disney’s media business for the future. Whether that’s evolving our streaming and digital products in new and immersive ways, powering worldwide advertising and distribution to maximize flexibility and efficiency, or delivering Disney’s unmatched entertainment and sports content, every day is a moment to make a difference to partners and to hundreds of millions of people around the world.

A few reasons why we think you’d love working for Disney Entertainment & ESPN Technology

• Building the future of Disney’s media business: DE&E Technologists are designing and building the infrastructure that will power Disney’s media, advertising, and distribution businesses for years to come.
• Reach & Scale: The products and platforms this group builds and operates delight millions of consumers every minute of every day – from Disney+ and Hulu, to ABC News and Entertainment, to ESPN and ESPN+, and much more.
• Innovation: We develop and execute groundbreaking products and techniques that shape industry norms and enhance how audiences experience sports, entertainment & news.

Job Summary:

The Lead Data Scientist is a senior technical leader responsible for driving innovation in personalization, experimentation, and large-scale data insight generation across ESPN’s streaming products. This role blends deep statistical expertise, strong technical execution, and exceptional communication skills to influence product strategy and guide a growing team of data scientists.

A successful candidate will lead the development of advanced experimentation frameworks, actionable dashboards, personalization insights, and scalable data science solutions that directly empower product managers, content programmers, and executive leadership. They will set technical direction, elevate data quality and standards, and champion automation and AI-assisted workflows to accelerate team productivity.

Responsibilities and Duties of the Role:

• Lead Technical Direction & Mentorship
  Provide technical leadership for the data science team, guiding junior and mid‑level data scientists through best practices in experimentation, modeling, analytics, and data storytelling.
• Drive Personalization Insights & Strategy
  Identify, analyze, and deliver high‑impact insights for ESPN personalization—including user behavior trends, recommendation system performance, and content engagement patterns—to influence product decisions.
• Architect & Execute Advanced Experimentation
  Design and analyze large‑scale A/B and multivariate experiments using rigorous statistical methods, power analysis, variance reduction techniques, and causal inference frameworks.
• Develop Scalable Data Insight Products
  Lead the design of automated dashboards, visualizations, and decision‑support tools, while partnering with Data Engineering to build durable, production‑ready data pipelines and science workflows.
• Lead High‑Impact, Cross‑Functional Projects
  Own end‑to‑end delivery of complex data science initiatives by collaborating with Product, Engineering, Content Programming, and Executive stakeholders, translating technical findings into actionable recommendations.

Minimum Qualification:

• 7+ years of experience in Data Science, Machine Learning, Statistics, or a related field, ideally supporting large-scale online platforms.
• Bachelors degree in Data Science, Computer Science, Statistics, or a relevant field or equivalent industry experience.
• Proven track record of delivering high-quality experimentation analyses and actionable insights that influenced product strategy.
• Deep expertise in statistical testing, causal inference, and experiment design (A/B testing, power analysis, sequential testing, etc.).
• Strong proficiency in Python, SQL, and modern ML/statistics libraries (pandas, scikit-learn, PyTorch/TensorFlow optional).
• Experience working with large-scale datasets in distributed computing environments (Spark, Databricks, Snowflake, etc.).
• Strong familiarity with data engineering best practices and building durable data science assets on top of production-grade data.
• Demonstrated success with dashboarding tools (Tableau, Looker, Mode) and crafting data stories for a variety of stakeholders.
• Experience applying automation and AI-driven tools to streamline workflows, improve standardization, and optimize productivity.
• Exceptional communication skills, especially in translating technical analyses into compelling stories for product managers and executives.
• Ability to lead projects with high ambiguity and cross-functional complexity.

Preferred qualification:

• Experience with personalization algorithms, recommender systems, or ranking models.
• Familiarity with streaming or media tech ecosystems.
• Advanced degree  in Data Science, Computer Science, Statistics, or a relevant field or equivalent industry experience

The hiring range for this position in Los Angeles, CA area is $155,700 - $208,700 per year, San Francisco is $170,500 - $228,600 per year, and New York City is $163,100 - $218,700. The base pay actually offered will take into account internal equity and also may vary depending on the candidate’s geographic region, job-related knowledge, skills, and experience among other factors. A bonus and/or long-term incentive units may be provided as part of the compensation package, in addition to the full range of medical, financial, and/or other benefits, dependent on the level and position offered.