Job Posting Title:
Lead Data Scientist
Req ID:
Job Description:
Product Engineering is a unified team responsible for the engineering of Disney Entertainment & ESPN digital and streaming products and platforms. This includes product engineering, media engineering, quality assurance, engineering behind personalization, commerce, lifecycle, and identity.
News & Entertainment Machine Learning (N&E ML) team is responsible for building robust data pipelines and advanced machine learning platforms that deliver personalized experiences to users across Disney's News & Entertainment portfolio including ABC News, ABC Entertainment, National Geographic, Marvel, and Disney Studios. Our services leverage machine learning models to enable real-time content personalization and targeted distribution across web, mobile, and connected TV platforms, ensuring that users receive the most relevant and engaging content tailored to their interests. Our mission is to drive seamless, resilient, and low-latency personalized content delivery at scale, while continuously advancing our ML infrastructure and recommendation algorithms across one of the world's most iconic collections of entertainment brands.
As a Lead Data Scientist, you will act as the bridge between data and product decisions for the N&E ML Platform, ensuring that machine learning and personalization investments translate into measurable business impact across Disney's News & Entertainment portfolio. You will conduct exploratory data analysis, design and evaluate experiments, and define the success metrics used to judge model and product performance. You will partner closely with Machine Learning Engineers on feature design, drift detection, and model evaluation, translating data insights into concrete, actionable recommendations for product and engineering stakeholders. Your impact will be measured by how effectively you turn data into decisions that improve the guest experience across ABC News, ABC Entertainment, National Geographic, Marvel, and Disney Studios.
Responsibilities:
- Exploratory Data Analysis & Insights: Conduct exploratory data analysis (EDA) across user, content, and engagement data to identify patterns, trends, and behavioral insights across the N&E portfolio (ABC News, ABC Entertainment, National Geographic, Marvel, and Disney Studios).
- Experimentation & A/B Testing: Design, implement, and evaluate A/B tests and other controlled experiments to validate product and personalization changes, applying sound statistical methodology to ensure results are reliable and actionable.
- Success Metrics & Model Evaluation: Define success metrics for ML-driven features and measure model performance against them, ensuring that model improvements are grounded in measurable, statistically valid outcomes.
- Partnership with ML Engineering: Partner closely with Machine Learning Engineers on feature design, drift detection, and model evaluation, acting as the analytical counterpart that ensures models remain accurate and relevant as data and user behavior evolve.
- Translating Insights into Action: Translate data insights into clear, actionable product recommendations, working with product managers, designers, and engineering stakeholders to prioritize changes with the greatest expected business impact.
- Statistical Analysis & Reporting: Apply statistical analysis using Python, SQL, and PySpark to large-scale datasets, and leverage tools such as Adobe Analytics to understand user behavior and content performance across brands.
- Bridging Data and Product: Act as the bridge between data and product decisions, ensuring that ML and personalization improvements translate into measurable business impact for guests across the N&E portfolio.
Basic Qualifications- Bachelor's degree in computer science, Statistics, Mathematics, Economics, or a comparable quantitative field of study, and/or equivalent work experience
- 7+ years of experience in data science, analytics, or a related field, including experience partnering directly with engineering and product teams
- Strong proficiency in Python, SQL, and PySpark for large-scale data analysis and manipulation
- Deep experience with cloud data platforms such as AWS, Databricks, or Snowflake
- Deep experience with statistical analysis and experimentation, including designing, running, and interpreting A/B tests
- Demonstrated ability to conduct exploratory data analysis (EDA) and translate patterns in user behavior into clear, actionable insights
- Experience defining success metrics and measuring model performance in partnership with Machine Learning Engineers, including feature design, drift detection, and model evaluation
- Proven ability to translate data insights into product recommendations that influence roadmap and prioritization decisions
- Experience with Adobe Analytics or comparable web/product analytics platforms
- Experience working with large-scale content or media platforms serving millions of consumers
- Experience with cloud infrastructure, preferably AWS (Step Functions, Lambda, Glue, SQS, SNS, Personalize)
- Experience with data visualization tools (e.g., Tableau, Looker) for communicating insights to stakeholders
- Strong communication skills, with the ability to present findings clearly to both technical and non-technical stakeholders
- Experience working in Agile/Scrum environments and collaborating across product, engineering, and design teams
Preferred Qualifications- Experience with agentic AI workflows and frameworks (e.g. LangGraph, AutoGen, CrewAI) and applying them to automate complex ML and data engineering tasks
- Familiarity with AI-assisted development tools such as Claude, Cursor, or GitHub Copilot to accelerate software development lifecycle and engineering productivity
- Familiarity with prompt engineering, fine-tuning, and evaluation frameworks for large language models in production environments
- Experience with MLOps platforms and modern model lifecycle management tools (e.g. MLflow, SageMaker, Vertex AI)
- Contributions to internal knowledge-sharing, conference talks, or publications related to data science or experimentation
The hiring range for this position in LA is $$155,700 - $208,700 per year. 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.
Job Posting Segment:
Product Engineering
Job Posting Primary Business:
PE - Streaming Backend
Primary Job Posting Category:
Data Science
Employment Type:
Full time
Primary City, State, Region, Postal Code:
Glendale, CA, USA
Alternate City, State, Region, Postal Code:
Date Posted:
2026-09-03
