Data Scientist, Connected TV ROI Measurement

About the position

Connected TV (CTV) has quickly become a dynamic, fast-growing surface for YouTube. YouTube's Connected TV Data Science team plays a pivotal role in fueling this growth by providing data-backed insights that directly drive the technical and business roadmaps. In this role, with the support of a technical lead, you will partner with Product Management, Engineering, and Marketing leaders on CTV to unlock paid subscriber growth with data-driven insights on the return on investment (ROI) and headroom for strategic investments across marketing, partnerships, offers, and OEM investments. YouTube/Video Global Solutions is the link between Google video products and sales. Our mission is to fuel innovation that keeps YouTube and Video free and accessible to the world. We do this by translating global market needs into meaningful product solutions that drive business results for content partners and customers.

Responsibilities

• Work with Marketing partners to evaluate and improve YouTube TV's Marketing Mix Models (MMM). Help shape how results are shared with leadership, influencing YouTube Marketing spend every year.
• Support matched market testing (e.g. geo experiments) for Sunday Ticket marketing spend. Deliver insights and make recommendations to CTV leadership based on experiments.
• Determine opportunities on an OEM basis across YouTube's main app and YouTube TV. Support experiments to measure efficacy of remote buttons and other OEM placements.
• Work across technical and marketing teams to design experiments to understand the ROI of acquisition and retention offers across YouTube's CTV products. Analyze efficacy between broad and targeted (i.e. user specific) offers.
• Work with data science teammates to refine LTV estimates across CTV products (e.g., YouTube TV, Sunday Ticket, Premium Channels). Support LTV-based applications of internal marketing.

Requirements

• Bachelor's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field.
• 5 years of work experience with analysis applications (extracting insights, performing statistical analysis, or solving business problems), and coding (Python, R, SQL) (or 2 years work experience plus a Master's degree).
• 2 years of experience working with Marketing Mix Models.
• Experience with matched market testing, A/B Testing, Geo Experiments, user-ablation studies, basic statistics, and regression analysis.

Nice-to-haves

• Master's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field.
• 5 years of work experience with analysis applications (e.g., extracting insights, performing statistical analysis, or solving business problems), and coding (e.g., Python, R, SQL).

Benefits

• Bonus
• Equity
• Health benefits