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Marketing science – a sub-team within marketing analytics at Disney Streaming Services (Hulu, Disney+, and ESPN) – is in search of an analyst to run marketing mix models (MMM) and associated ancillary analysis. This position will work as part of a team focused primarily on econometric modeling, which also provides support for downstream practices used to inform marketing investment and plays a hands-on role in modeling efforts.
The ideal candidate has a substantial quantitative skill set with direct experience in marketing science practices (MMM, attribution modeling, testing / experimentation, etc.), and should serve as a strong mentor to analysts, helping to onboard new talent in support of wider company goals. Technical acumen as well as narrative-building are integral to the success of this role.
Responsibilities
Build, sustain and scale econometric models (MMM) for Disney Streaming Services with support from data engineering and data product teams
Quantify Return on Ad Spend, determineoptimal spend range across the portfolio, identify proposed efficiency caps by channel, set budget amounts and inform subscriber acquisition forecasts
Support ad hoc strategic analysis to provide recommendations that drive increased return on spend through shifts in mix, flighting, messaging and tactics, and that help cross-validate model results
Provide insights to marketing and finance teams, helping to design and execute experiments to move recommendations forward based on company goals (e.g., subscriber growth, LTV, etc)
Support long-term MMM (et.al.) automation, productionalization and scale with support from data engineering and product
Build out front-end reporting and dashboarding in partnership with data product analysts and data engineers to communicate performance metrics across services, markets, channels and subscriber types
Basic Qualifications
Bachelors degree in Data Science, Computer Science, Engineering, Mathematics, Econometrics, Statistics or related field
5+ years of experience in a marketing science / analytics role with understanding of measurement and optimization best practices
Coursework or direct experience in applied econometric modeling, ideally in support of measure marketing efficiency and optimize spend, flighting and mix to maximize return on ad spend (i.e., MMM)
Exposure / understanding of media attribution practices for digital and linear media, the data required to power them and methodologies for measurement
Understanding of incrementality experiments to validate model recommendations and gain learnings on channel/publisher efficacy
Exposure to / familiarity with with BI/data concepts and experience building out self-service marketing data solutions
Experience in SQL as well as statistical modeling platforms (Python, R, etc.)
#DISNEYANALYTICS
#DISNEYTECH
The hiring range for this position in New York, NY & Seattle, WA is $145,500 to $195,000 per year. Santa Monica, CA is $138,900 to $186,200 per year, San Francisco, CA is $152,100 to $203,900 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.
Job ID: 10128241
Location: New York,New York
Job Posting Company: Disney Direct to Consumer
The Walt Disney Company and its Affiliated Companies are Equal Employment Opportunity employers and welcome all job seekers including individuals with disabilities and veterans with disabilities. If you have a disability and believe you need a reasonable accommodation in order to search for a job opening or apply for a position, email [email protected] with your request. This email address is not for general employment inquiries or correspondence. We will only respond to those requests that are related to the accessibility of the online application system due to a disability.
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