Senior Marketing Data Scientist

Marketing Science is an applied science team within The Walt Disney Studios 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 Studios.  Depending on their backgrounds and interests, they may engage in market research, experimentation, forecasting, causal measurement, optimization, or data-related automation and data science product development.  Marketing Science is a part of The Walt Disney Studios Performance Marketing 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.

Job Responsibilities: 

A person in this role is an individual contributor who has already developed some expertise through meaningful experience in their functional areas so as to be able to carry efforts in those areas within at least one major project with less supervision.  A person in this role is expected to be developing knowledge in media, marketing, and entertainment.

• 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
• 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 science products using foundational data sets that are regularly refreshed by data engineering teams
• Developing and maintaining code for data science products in consultation with engineering teams
• Optimizing code to make data science workflows run more efficiently
• Consulting regularly with technology partners to ensure that proper data science tooling and platforms are available
• 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 science products
• Providing documentation and instruction to other scientists, engineers, or analysts about how to use data science 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 science 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 the health and deployment of statistical and machine learning models and optimization routines embedded in data science products
• Building machine learning models, statistical models, or optimization routines for the purposes of automating and scaling tasks as part of data science products
• Using code and data science best practices to implement 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
• Coordinating work with other science and technology teams at The Walt Disney Company

Basic Education:

• Bachelor’s degree in Mathematics, Statistics, Data Science or comparable field of study, and/or equivalent work experience
• Demonstrated academic achievement in statistics and probability—typically involving graduate-level coursework
• Relevant areas include (but are not limited to) statistics, data science, applied mathematics, operations research, engineering, and computer science 
   

Basic Qualifications:

• 5+ years of experience
• Sufficient professional experience working specifically within their functional area(s) to carry out related tasks with only some supervision
• Some demonstrated knowledge of media and marketing as well as a desire to learn more
• Desire to learn about the entertainment / media industries
• Reasonable level of business acumen in addition to very strong technical skills
• Proven creative problem-solving, decision-making and critical thinking skills
• Demonstrated outstanding interpersonal skills, including ability to partner with others to handle multiple priorities in a rapidly changing environment
• Demonstrated strong written and verbal communication skills
• Strong leadership skills for a technical position
• Ability to work independently as well as across teams in a diverse, international, collaborative environment
• Proven ability to organize, prioritize, and balance concurrent projects and sustainment activities
• Proficiency in acquiring, organizing, cleansing, manipulating, and merging large volumes of data
• Proficiency in performing exploratory quantitative analysis
• Proficiency in fitting, evaluating, and interpreting relevant statistical or machine learning models
• Advanced proficiency with Python
• Proficiency with SQL
• Demonstrated experience using big data technologies for data science—particularly Spark
• Demonstrated experience working across technical functions
• Demonstrated experience working with complicated systems
• Familiarity with Tableau or other data visualization tool
• Familiarity with cloud computing services
• Familiarity with CI/CD and GitLab or GitHub

Preferred Qualifications:

• Graduate degree (Master’s or Doctorate)—with significant graduate-level academic exposure to formal or quantitative methods and 3+ years of experience
• Advanced proficiency with SQL
• Advanced proficiency with fitting, evaluating, and interpreting relevant statistical and machine learning models
• Proficiency with Tableau or other data visualization tool
• Advanced proficiency in acquiring, organizing, cleansing, manipulating, and merging large volumes of data
• Familiarity with the martech and adtech ecosystem