Sr Analytics Engineer

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 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: 

Members of the Marketing Science team generally fall within one or more functional areas as described in the Analytics Specializations section below.  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.

Analytics Specializations:

Analytics 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 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 data or decision scientists as appropriate and necessary to ensure that best data and decision science practices are followed
• Working directly with data scientists and decision scientists 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 Computer Science, Information Systems, Software, Electrical or Electronics Engineering, or comparable field of study, and/or equivalent work experience
• Demonstrated academic achievement in statistics and probability—typically involving graduate-level coursework
• Analytics Engineering and Technology: relevant areas include (but are not limited to) computer science and applied mathematics

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
• People working in Analytics Engineering and Technology need to be able to work across technical functions and understand how complicated systems work
• 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
• Proficiency with Python
• Demonstrated experience with SQL
• Familiarity with Tableau or other data visualization tool
• Familiarity with cloud computing services
• Familiarity with CI/CD and GitLab or GitHub

Preferred Education

• Graduate degree (Master’s or Doctorate)—with significant graduate-level academic exposure to formal or quantitative methods

Preferred Qualifications

• Advanced proficiency with SQL
• Advanced proficiency with R or Python
• Advanced proficiency with fitting, evaluating, and interpreting relevant statistical and machine learning models
• Proficiency with Tableau or other data visualization tool
• Demonstrated experience using big data technologies for data science—particularly Spark
• Proficiency in acquiring, organizing, cleansing, manipulating, and merging large volumes of data
• Familiarity with the martech and adtech ecosystem

The hiring range for this position in Burbank, CA is $104,600.00 to $140,200.00 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.