Associate Marketing Data Scientist

The Walt Disney Company•Celebration, FL

1d•$92,900 - $124,500•Onsite

About The Position

Marketing Science is an applied science team within The Walt Disney Company Marketing organization. The team is interdisciplinary and cross-functional. Members of the team draw on knowledge and expertise from a wide range of academic disciplines, but primarily in areas related to applied mathematics and the social sciences, in order to advance data-driven marketing at The Walt Disney Company. Depending on their backgrounds and interests, they may engage in market research, experimentation, forecasting, causal measurement, optimization, or data-related automation and data product development. Marketing Science is a part of Performance Marketing at The Walt Disney Company and is closely integrated with Performance Marketing operations. Members of the Marketing Science team generally learn about the advertising and marketing technologies that connect these operations in order to find opportunities to improve marketing effectiveness. We are seeking an Associate Marketing Data Scientist to join the Marketing Science team at Disney. Members of the Marketing Science team generally fall within one or more functional areas as described in the Specializations section below. A person in this role is an individual contributor who is developing expertise in one or more functional area and has attained significant capabilities so as to be able to help complete tasks within those functional areas with supervision. You are expected to be developing knowledge in media, marketing, and entertainment. The role reports to a VP, Marketing Science and is based in Celebration, FL

Requirements

Desire to learn about media and marketing and the overall entertainment / media industries
Demonstrated experience with organizing, prioritizing, and balancing concurrent projects and sustainment activities
Demonstrated experience with acquiring, organizing, cleansing, manipulating, and merging large volumes of data
Demonstrated experience with performing exploratory quantitative analysis
Demonstrated experience with fitting, evaluating, and interpreting relevant statistical or machine learning models
Demonstrated experience with Python
Familiarity with SQL, using GenAI-powered tools for coding, Tableau or other data visualization tools, cloud computing services and CI/CD and GitLab or GitHub
Desire to learn about the martech and adtech ecosystem
Strong business acumen in addition to strong technical skills
Demonstrated potential for developing strong creative problem-solving, decision-making and critical thinking skills
Demonstrated strong interpersonal skills, including ability to partner with others to handle multiple priorities in a rapidly changing environment
Demonstrated strong written and verbal communication skills
Ability to work independently as well as across teams in a diverse, international, collaborative environment

Nice To Haves

Proficiency with Python and experience with SQL
Demonstrated experience using GenAI-powered tools for coding
Demonstrated experience with Tableau or other data visualization tools
Demonstrated experience using big data technologies for data science—particularly Spark
Proficiency in acquiring, organizing, cleansing, manipulating, and merging large volumes of data

Responsibilities

Overseeing or carrying out all aspects of quality market research, including overseeing proper sampling, assigning sample weights, participating in survey / research design, and validating survey programming.
Designing innovative research studies that uncover not only consumer trends and behavior but also the beliefs, values and motivations of consumers
Using discrete choice models and other advanced analytic techniques to better understand the way consumers make decisions
Using unsupervised learning models and other advanced analytic techniques to produce and evaluate data-driven customer segmentations for various marketing purposes
Synthesizing audience and consumer insights into compelling narratives for business stakeholders in The Walt Disney Company Marketing organization
Overseeing consumer research collected as part of brand lift studies
Coordinating work with other research teams at The Walt Disney Company
Troubleshooting problems with existing media measurement solutions, including problems that arise from changes in the martech or adtech measurement ecosystem (e.g. iOS14 update, cookie deprecation, etc.)
Consulting with business stakeholders within TWDC media team (or adjacent teams within TWDC Marketing) to design business processes or campaign architectures that achieve better results on various media platforms including DSPs (DV360, The Trade Desk, Amazon DSP, etc.) or walled gardens (YouTube, Facebook, Twitter, TikTok, etc.)
Consulting with business stakeholders within TWDC media team (or adjacent teams within TWDC Marketing) to precisely formulate media business problems that might benefit from data-driven solutions
Using knowledge of media measurement—including, but not limited to knowledge of pixels, SDKs, server-to-server integrations, media platform APIs, and identity graphs—to design measurement solutions for media business problems
Translating media business problems into formal problems that can be solved by technical teams
Validating whether proposed solutions and existing products successfully address media business problems
Overseeing design, execution, and analysis of A/B tests in order to evaluate the effectiveness of media / marketing exposure across different dimensions
Designing, interpreting or otherwise using formal models (e.g. marketing mix models, attribution models) to measure causal effects of marketing or media
Building financial valuation models of marketing or media performance in order to demonstrate the value created by application of scientific approaches or uncover additional areas for improvement
Using concepts and principles of economics to better understand the effects of competition on marketing
Using concepts and principles of economics or finance to better understand the effects of marketing on the lifetime value of movies
Using knowledge of statistics, machine learning, and AI to solve technical and research problems, including problems related to experimental and research design
Developing and interpreting the results of new formal models to forecast or predict business outcomes
Developing and interpreting the results of new formal models (e.g; marketing mix models, attribution models, etc) to measure causal effects of marketing efforts or paid media
Overseeing the maintenance and improvement of existing statistical and machine learning models
Prototyping data pipelines or tools to automate the creation and/or deployment of knowledge gained from statistical models, machine learning models, or artificial intelligence
Formulating and solving optimization problems
Applying understanding of concepts and principles of optimization to evaluate and improve media and marketing performance
Formulating and solving formal optimization problems
Effectively leveraging big data and cloud computing technologies to address business questions
Architecting, designing, and building data products using foundational data sets that are regularly refreshed by data engineering teams
Developing and maintaining code for data products
Consulting regularly with business stakeholders and data product owners or managers on current data assets and data strategy in order to ensure that the right data is acquired, maintained, and used properly to solve recurring media and marketing problems within the entertainment and media industries
Leveraging business knowledge from business stakeholders to provide specifications and requirements to technology and data engineering teams for ingesting, transforming, and cleaning foundational data sets that can be leveraged downstream for building data products
Providing documentation and instruction to other scientists, engineers, or analysts about how to use data products to automate and scale data-retrieval, generation of data results, data-driven recommendation, or data-driven decision-making
Leveraging business knowledge from business stakeholders to integrate and transform data from various foundational data sets as required to create successful data products
Using code and technology to build data pipelines or tools to automate the creation and/or deployment of knowledge gained from statistical models, machine learning models, or artificial intelligence
Monitoring and overseeing the deployment, maintenance, and improvement of the statistical and machine learning models and optimization routines embedded in data products
Building machine learning models, statistical models, or optimization routines—especially for the purposes of automating and scaling tasks—while leveraging the expertise of others to ensure that best data and decision science practices are followed
Implementing bespoke, rigorous methodologies in order to systematically solve marketing problems in repeatable ways
Working directly with business stakeholders, analysts, and researchers to develop code to implement bespoke, rigorous analytic or business processes in order to systematically provide insights or recommendations in repeatable ways
In concert with the Marketing Technology team, designing and building GenAI‑powered data products that transform raw, multi‑modal data into actionable insights, predictions, and user‑facing experiences
Architecting end‑to‑end AI systems that combine classical ML, deep learning, vector search, retrieval‑augmented generation (RAG), and other techniques to deliver reliable, scalable intelligence
Translating ambiguous product and business problems into AI‑first solutions, defining data requirements, modeling approaches, and success metrics
Building and maintaining data pipelines and feature stores that support real‑time and batch inference for GenAI and ML workloads
Implementing evaluation, monitoring, and observability frameworks for GenAI systems, including hallucination detection, bias analysis, latency/cost optimization, and model drift
Coordinating work with other science and technology teams at The Walt Disney Company