Staff Data Scientist
- Burbank, CA
- $152,200-204,100 per year
- Permanent
- Full-time
- Opportunity Discovery and Diagnostic Investigation – Engage segment partners to surface hypotheses, perform data sleuthing to size value, and craft lean proofs of concept to validate ROI in weeks, not months.
- Experiment Design and Insight Reporting – Structure A/B tests or causal studies, measure impact, and package results into clear, decision ready insights for executives and creative leaders.
- Data Science and ML Delivery – Design, train, and deploy predictive models, statistical analyses, and machine learning systems that drive guest and business impact.
- Data Flywheel and MLOps – Stand up cloud native pipelines, feature engineering workflows, and monitoring that keep models healthy post launch.
- Stakeholder Storytelling – Translate complex findings into compelling narratives and decision frameworks for product, creative, and executive audiences.
- People Leadership – Recruit, mentor, and coach 1–2 data scientists/engineers; codify reusable assets and best practices.
- Responsible AI and Governance – Ensure all work aligns with Disney’s Responsible AI guardrails in partnership with Legal, Privacy, and Security.
- BS in advanced Mathematics, Statistics, Data Science in comparable field of study + 7 years of experience or PhD in advanced Mathematics, Statistics, Data Science in comparable field of study + 3 years of experience.
- Expert proficiency in Python, SQL, and modern ML/DL libraries (scikit learn, TensorFlow, PyTorch); solid grounding in statistical modeling, experiment design, and causal inference.
- Hands on experience with AWS, GCP, or Azure and big data frameworks such as Snowflake, Spark, or Databricks.
- Proven ability to move from whiteboard idea to production solution and influence cross functional teams through data storytelling.
- Strong software engineering fundamentals (version control, testing, CI/CD); familiarity with data visualization or experimentation platforms (e.g., Looker, Tableau, Optimizely).
- Domain knowledge in media, streaming, sports, parks, or consumer products.
- Experience with LLMs, vector search, and retrieval augmented generation.
- Background in causal inference or experimentation platforms.
- Prior experience hiring or leading small technical teams.
- Reports directly to the Director, ML Architecture & Engineering and partners daily with the Manager, AI Enablement and Staff Architect to align technical design with product outcomes.