Senior Data Scientist, Marketing Analytics (Mobile)

Gametime United

5d•$192,313 - $226,250•Remote

About The Position

Our Marketing Analytics team is a cross-functional group supporting all aspects of Gametime, partnering closely with User Acquisition to optimize mobile campaign performance across channels like Meta, TikTok, Reddit, and other paid platforms. We drive creative and spend efficiency through rigorous experimentation, advanced measurement, and granular channel analysis, and we work to strengthen the connection between platform-reported performance, attribution-based data, and internal customer economics. The team studies mobile cohorts to identify high-value opportunities across leagues, teams, performers, and user segments, with an eye toward maximizing lifetime value and durable growth. We're hiring a Senior Data Scientist to help build and scale the analytical frameworks that power mobile marketing at Gametime, from executive-level performance narratives down to campaign, creative, cohort, and audience-level diagnostics. The ideal candidate has hands-on experience with mobile marketing, paid social platforms, mobile attribution, experimentation, causal measurement, audience management, and financial profitability modeling in a marketplace or consumer mobile setting, and is comfortable moving fluidly between strategic and highly granular work. We hire based on impact and capability, not just years of experience. We encourage you to apply and your level will be fully determined and agreed in the interview process.

Requirements

7+ years of experience in marketing analytics, growth data science, mobile analytics, or a related field; Bachelor's degree in Data Science, Mathematics, Statistics, Computer Science, Economics, or a related field.
Prior experience at a mobile-first company, with deep understanding of mobile attribution, Apple ATT, MMPs, and privacy-aware measurement solutions.
Hands-on experience with Meta, TikTok, Reddit, or similar paid social platforms, analyzing performance at the campaign, creative, and cohort level.
Experience evaluating acquisition and retargeting performance through LTV, CAC, ROAS, payback windows, and profitability models.
Experience designing and interpreting marketing experiments or causal measurement studies, such as geo-lift tests and audience holdouts.
Experience building, managing, or analyzing user lists for paid marketing activation, with a strong grasp of segmentation, suppression logic, and saturation.
Strong foundation in statistics, with experience in experimentation, incrementality measurement, cohort analysis, and causal inference.
Experience analyzing creative performance and identifying fatigue to improve testing frameworks.
Proficiency in Python or R and SQL, along with hands-on experience with BI tools (Tableau, Sigma) and Mobile Measurement Partners (Adjust, AppsFlyer, etc.).
Strong communication skills, with the ability to present technical insights and attribution nuances in a way that supports executive decision-making.

Nice To Haves

Experience with Marketing Mix Modeling (MMM) or incrementality testing
Experience in ticketing, live events, marketplaces, or consumer mobile apps.
Experience working with highly seasonal businesses, event-driven demand, or shifting supply and pricing dynamics.

Responsibilities

Own the analytical frameworks for tracking mobile marketing effectiveness in a privacy-aware environment, bridging platform-reported data, attribution data, MMP data, and internal truth to support confident decisions despite measurement noise.
Own the end-to-end design and maintenance of marketing analytics dashboards in Sigma/Tableau, serving as a trusted source of truth for performance, user quality, payback, and profitability reporting.
Conduct granular analysis on campaign, ad set, ad, and creative performance (IPM, CPM, CPI, CAC, ROAS), providing data-driven recommendations and partnering with marketing to spot creative fatigue and winning assets.
Analyze mobile user cohorts to understand retention, monetization, payback, and LTV behaviors, identifying efficiency trends across leagues, teams, and acquisition sources to guide budget allocation.
Partner with marketing and finance to understand channel incrementality, profitability, and spend efficiency, building financial scenario models to inform where to scale, reduce, or reallocate spend.
Design, analyze, and interpret experiments to measure true channel incrementality and marketing lift, including geo-lift, PSA tests, and audience holdouts, translating results into practical recommendations.
Own analytical support for retargeting and audience strategy, building and maintaining user lists and improving segmentation to ensure programs drive incremental value rather than capturing organic demand.
Analyze how marketplace conditions, event demand, league mix, pricing, and seasonality influence acquisition efficiency, helping distinguish marketing execution shifts from broader marketplace dynamics.
Partner with leadership to translate complex analyses into clear recommendations on spend allocation, channel strategy, and growth investment, communicating tradeoffs and risks to support fast decisions.
Stay current on the evolving mobile privacy and attribution landscape (Apple ATT, MMP capabilities) to keep data science a competitive advantage in how Gametime measures and scales mobile growth.