Associate Marketing Data Scientist

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.

reports to a VP, Marketing Science and is based in Celebration, FL You Will /

As an Associate Marketing Data Scientist you will work within the following specializations: Research And Consumer Insights Specialization • 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 Marketing Measurement And Valuation Specialization • 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 Statistics, Data Science, and Optimization Specialization • 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 AI, ML, Analytics, and Data Engineering and Technology Specialization • 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