Senior Data Scientist

Posted 2 Days Ago
2 Locations
In-Office
142K-190K Annually
Senior level
Digital Media • Gaming • News + Entertainment • Sports
The Role
Conduct exploratory data analysis, run and interpret A/B tests, define and track product metrics, and support machine learning feature analysis and model evaluation. Analyze user, content, and engagement data using Python, SQL, and PySpark; monitor model performance and identify anomalies. Collaborate with product, design, engineering, and data science partners, communicating findings and recommendations to inform product decisions.
Summary Generated by Built In

Job Posting Title:

Senior Data Scientist

Req ID:

10158432

Job Description:

Technology is at the heart of Disney’s past, present, and future. Disney Entertainment and ESPN Product & Technology is a global organization of engineers, product developers, designers, technologists, data scientists, and more – all working to build and advance the technological backbone for Disney’s media business globally.

The team marries technology with creativity to build world-class products, enhance storytelling, and drive velocity, innovation, and scalability for our businesses. We are Storytellers and Innovators. Creators and Builders. Entertainers and Engineers. We work with every part of The Walt Disney Company’s media portfolio to advance the technological foundation and consumer media touch points serving millions of people around the world.

Here are a few reasons why we think you’d love working here:

  • Building the future of Disney’s media: Our Technologists are designing and building the products and platforms that will power our media, advertising, and distribution businesses for years to come.
  • Reach, Scale & Impact: More than ever, Disney’s technology and products serve as a signature doorway for fans' connections with the company’s brands and stories. Disney+. Hulu. ESPN. ABC. ABC News…and many more. These products and brands – and the unmatched stories, storytellers, and events they carry – matter to millions of people globally.
  • Innovation: We develop and implement groundbreaking products and techniques that shape industry norms, and solve complex and distinctive technical problems.

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.

The 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 Senior Data Scientist, you will conduct exploratory data analysis and support experimentation for the N&E ML Platform, helping ensure that machine learning and personalization work is grounded in reliable data and sound statistical practice. Under the guidance of the Lead Data Scientist and senior stakeholders, you will run A/B tests, analyze results, and help define and track success metrics for specific product areas or brands within Disney's News & Entertainment portfolio. You will work closely with Machine Learning Engineers on feature analysis and model evaluation, and translate your findings into clear recommendations for your immediate team. Your impact will be measured by the quality and reliability of the analyses you produce and how effectively they inform decisions within your area of focus.

Responsibilities:

  • Exploratory Data Analysis: Conduct exploratory data analysis on user, content, and engagement data within an assigned brand or product area, surfacing patterns and trends for review with senior data scientists and stakeholders.
  • A/B Test Execution & Analysis: Run A/B tests and other controlled experiments under established methodology, analyze results, and summarize findings clearly for your immediate team.
  • Metric Tracking: Help define and track success metrics for specific features or product areas, and monitor model performance against them, escalating anomalies to senior team members.
  • Support for ML Engineering: Work with Machine Learning Engineers on feature analysis and model evaluation for your assigned area, providing data support for drift detection and performance reviews.
  • Insight Communication: Translate analysis into clear findings and recommendations for your immediate team, supporting (rather than leading) broader product and roadmap discussions.
  • Statistical Analysis: Apply statistical analysis using Python, SQL, and PySpark to datasets within your area of focus, using tools such as Adobe Analytics to support behavioral analysis.
  • Collaboration & Growth: Collaborate with product, design, and engineering partners on assigned initiatives, and develop toward broader ownership of experimentation and metrics design over time.

Basic Qualifications

  • Bachelor’s degree in Computer Science, Statistics, Mathematics, Economics, or a comparable quantitative field of study, and/or equivalent work experience
  • 5+ years of experience in data science, analytics, or a related field
  • Proficiency in Python, SQL, and PySpark for data analysis and manipulation
  • Working knowledge of statistical analysis and experimentation, including running and interpreting A/B tests under established methodology
  • Ability to conduct exploratory data analysis (EDA) and identify patterns in user behavior data
  • Experience working with cloud data platforms such as AWS, Databricks, or Snowflake
  • Clear written and verbal communication skills, with the ability to summarize findings for an immediate team
  • Experience working in Agile/Scrum environments and collaborating with engineering and product partners

Preferred Qualifications

  • Experience with Adobe Analytics or comparable web/product analytics platforms
  • Exposure to large-scale content or media platforms
  • Familiarity with data visualization tools (e.g., Tableau, Looker)
  • Basic familiarity with machine learning concepts sufficient to support ML Engineers on feature analysis and evaluation
The hiring range for this position in LA is $141,900 - $190,300 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:

USA - NY - 7 Hudson Square

Date Posted:

2026-09-03

Skills Required

  • Bachelor's degree in Computer Science, Statistics, Mathematics, Economics, or a comparable quantitative field, or equivalent work experience
  • 5+ years of experience in data science, analytics, or a related field
  • Proficiency in Python, SQL, and PySpark for data analysis and manipulation
  • Working knowledge of statistical analysis and experimentation, including running and interpreting A/B tests
  • Ability to conduct exploratory data analysis and identify patterns in user behavior data
  • Experience working with cloud data platforms such as AWS, Databricks, or Snowflake
  • Clear written and verbal communication skills
  • Experience working in Agile/Scrum environments and collaborating with engineering and product partners
  • Experience with Adobe Analytics or comparable web/product analytics platforms
  • Exposure to large-scale content or media platforms
  • Familiarity with data visualization tools such as Tableau or Looker
  • Basic familiarity with machine learning concepts sufficient to support feature analysis and evaluation

The Walt Disney Company Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about The Walt Disney Company and has not been reviewed or approved by The Walt Disney Company.

  • Pay Growth & Progression Recent union agreements raised wage floors for large groups of park cast members—e.g., Disneyland’s $24/hour minimum rising to $26 over the contract and Walt Disney World’s path from $18 toward about $20–$20.50 by 2026—signaling upward movement in hourly pay. These steps are described as meaningful improvements for many frontline roles.
  • Healthcare Strength Company materials outline medical, dental, and vision coverage for many full‑time roles, wellness resources, and (in Central Florida) access to Centers for Living Well clinics and pharmacy. References to mental‑health support and paid time off reinforce a strong core health offering.
  • Wellbeing & Lifestyle Benefits Complimentary theme‑park admission and discounts on hotels, dining, merchandise, and recreation are positioned as signature perks. Education support through Disney Aspire adds notable lifestyle value for eligible hourly employees.

The Walt Disney Company Insights

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The Company
HQ: Burbank, CA
219,548 Employees
Year Founded: 1923

What We Do

The Walt Disney Company is a leading diversified international family entertainment and media enterprise that operates through segments including entertainment, sports, and experiences.

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