Associate Marketing Data Scientist

The Walt Disney Company • Celebration, FL

4d • Onsite

About The Position

The Associate Marketing Data Scientist joins the Marketing Science team within The Walt Disney Company’s Marketing organization and Performance Marketing group. The interdisciplinary team applies methods from applied mathematics and social sciences to advance data-driven marketing, working across market research, experimentation, forecasting, causal measurement, optimization, automation, and data product development. Team members build knowledge of advertising and marketing technologies and are expected to develop expertise in media, marketing, and entertainment. This is an individual-contributor role for someone developing expertise in one or more functional areas who can complete work with supervision. The position reports to a VP, Marketing Science and is based in Celebration, Florida.

Depending on specialization, the role may involve consumer research and segmentation; media measurement, valuation, experimentation, and causal analysis; statistics, machine learning, forecasting, and optimization; or AI, ML, analytics, data engineering, and technology. Work includes collaborating with stakeholders and other science and technology teams, translating business needs into research or technical solutions, and developing or improving analytical models, data products, and automated processes. In the AI and data product area, responsibilities can include GenAI-powered products and end-to-end AI systems that use methods such as retrieval-augmented generation, vector search, and classical machine learning.

The hiring range in Celebration, Florida is $92,900 to $124,500 per year. Actual base pay may vary based on factors including internal equity, geographic region, job-related knowledge, skills, and experience. A bonus and/or long-term incentive units may be offered in addition to medical, financial, and other benefits, depending on the level and position.

Requirements

• Desire to learn about media, marketing, and the entertainment and media industries.
• Experience organizing, prioritizing, and balancing concurrent projects and sustainment activities.
• Experience acquiring, organizing, cleansing, manipulating, and merging large volumes of data.
• Experience performing exploratory quantitative analysis.
• Experience fitting, evaluating, and interpreting relevant statistical or machine learning models.
• Experience with Python.
• Familiarity with SQL, GenAI-powered coding tools, Tableau or other data visualization tools, cloud computing services, CI/CD, and GitLab or GitHub.
• Desire to learn about the marketing technology and advertising technology ecosystem.
• Strong business acumen and technical skills.
• Potential to develop strong creative problem-solving, decision-making, and critical-thinking skills.
• Strong interpersonal skills and ability to partner with others while handling multiple priorities in a rapidly changing environment.
• Strong written and verbal communication skills.
• Ability to work independently and across teams in a diverse, international, collaborative environment.
• Bachelor’s degree with significant academic exposure to formal or quantitative methods.
• Demonstrated academic achievement in statistics and probability, typically including graduate-level coursework.
• Further academic achievement in a field related to the selected specialization, such as psychology, sociology, marketing, cognitive science, economics, applied statistics, business, statistics, data science, applied mathematics, operations research, or computer science.

Nice To Haves

• Graduate degree (Master’s or Doctorate) with significant graduate-level academic exposure to formal or quantitative methods.
• Proficiency with Python and experience with SQL.
• Experience using GenAI-powered tools for coding.
• Experience with Tableau or other data visualization tools.
• Experience using big data technologies for data science, particularly Spark.
• Proficiency acquiring, organizing, cleansing, manipulating, and merging large volumes of data.

Responsibilities

• Conduct or oversee quality market research, including sampling, sample weighting, research and survey design, and validation of survey programming.
• Design research studies to uncover consumer trends, behaviors, beliefs, values, and motivations.
• Use discrete choice models, unsupervised learning, and other advanced analytical techniques to understand consumer decisions and develop customer segmentations.
• Synthesize audience and consumer insights into clear narratives for business stakeholders.
• Oversee consumer research conducted as part of brand lift studies and coordinate with other research teams.
• Troubleshoot media measurement solutions, including issues arising from changes in the marketing technology and advertising technology ecosystem.
• Consult with media and marketing stakeholders to design business processes and campaign architectures that improve results across media platforms.
• Formulate media business problems that may benefit from data-driven solutions and translate them into formal problems technical teams can solve.
• Design measurement solutions using knowledge of pixels, SDKs, server-to-server integrations, media platform APIs, and identity graphs.
• Validate proposed solutions and existing products against media business problems.
• Oversee the design, execution, and analysis of A/B tests evaluating marketing and media exposure.
• Design, interpret, or use marketing mix, attribution, and other formal models to measure causal effects of marketing or media.
• Build financial valuation models of marketing or media performance and apply economic concepts to understand competition and marketing effects on movie lifetime value.
• Use statistics, machine learning, and AI to address technical and research problems, including experimental and research design.
• Develop and interpret models to forecast business outcomes or measure causal effects of marketing and paid media.
• Oversee maintenance and improvement of statistical and machine learning models.
• Prototype data pipelines and tools to automate the creation or deployment of insights from statistical, machine learning, or AI models.
• Formulate and solve optimization problems and use optimization principles to evaluate and improve marketing and media performance.
• Use big data and cloud computing technologies to address business questions.
• Architect, design, build, and maintain data products and their code using foundational datasets.
• Consult with stakeholders and data product owners or managers about data assets and strategy to ensure data is acquired, maintained, and used appropriately.
• Provide specifications and requirements to technology and data engineering teams for ingesting, transforming, and cleaning foundational datasets.
• Document and explain data products so other scientists, engineers, or analysts can use them to automate data retrieval, analysis, recommendations, and decisions.
• Integrate and transform data from foundational datasets to build data products and automated pipelines.
• Monitor and oversee deployment, maintenance, and improvement of models and optimization routines embedded in data products.
• Build models and optimization routines, especially to automate and scale tasks, while following sound data and decision science practices with support from others.
• Implement rigorous, repeatable methodologies and analytic or business processes to provide insights and recommendations.
• Design and build GenAI-powered data products with the Marketing Technology team that turn raw multimodal data into insights, predictions, and user-facing experiences.
• Architect end-to-end AI systems combining methods such as classical ML, deep learning, vector search, and retrieval-augmented generation.
• Translate ambiguous product and business problems into AI-first solutions, defining data requirements, modeling approaches, and success metrics.
• Build and maintain data pipelines and feature stores for real-time and batch inference workloads.
• Implement evaluation, monitoring, and observability for GenAI systems, including hallucination detection, bias analysis, latency and cost optimization, and model-drift monitoring.
• Coordinate work with other science and technology teams at The Walt Disney Company.

Benefits

• Health benefits
• Savings benefits
• Educational opportunities
• Disney-specific extras
• A bonus and/or long-term incentive units may be provided, depending on the level and position.
• Medical and financial benefits

What This Job Offers

• Job Type: Full-time
• Career Level: Entry Level