Lead the data science function for mobile app performance at the intersection of machine learning and programmatic advertising. Responsibilities include building signal enrichment pipelines, developing production-grade predictive models from event data, partnering with GTM teams for insights, conducting deep-dive analyses to influence product and engineering decisions, developing predictive modeling frameworks, acting as the senior data science voice in product discussions, diagnosing system health issues, defining success metrics, designing experiments, and applying causal inference methods. Requires 5+ years of data science experience focused on ML model development and statistical inference, proficiency in Python and SQL, experience with large-scale data environments (Spark, Hadoop, Hive), strong foundation in experimental design and causal inference, and experience with ML algorithms such as gradient boosted trees and deep learning. Preferred qualifications include experience in mobile advertising or programmatic ad tech, familiarity with mobile measurement and attribution, collaboration with ML engineering/product teams, and an advanced degree in a quantitative discipline. The role is full-time, senior level, and hybrid based in Redwood City, California. Benefits include paid leave, healthcare, commuter benefits, wellness programs, unlimited discretionary time off, and in-office catered lunches. Salary range is $225,000 to $250,000 USD.
What you'll do
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Build signal enrichment pipelines leveraging contextual signals, behavioral data, and mobile attribution frameworks
Develop production-grade predictive models based on event data (clicks, installs, in-app events, retention)
Partner with GTM teams to translate metric frameworks into buyer-facing insights and predictive models
Conduct deep-dive analysis to influence product and engineering decisions by querying large datasets and producing actionable insights
Develop predictive modeling frameworks to quantify performance gains from product hypotheses before they ship
Act as the senior data science voice in product discussions, providing partner-level insight and analytical rigor
Understand changes and drivers across the mobile ecosystem, diagnose issues, identify inefficiencies, and track system metrics
Work with product and engineering to define success metrics, design experiments, and evaluate new features pre- and post-launch
Design experiment frameworks and causal inference methods that produce reliable, unbiased signals for product and business decisions
Requirements
5+ years of hands-on data science experience, with a focus on ML model development, statistical inference, and production-grade analysis
Deep fluency in Python and SQL; experience with large-scale data environments (Spark, Hadoop, Hive, or equivalent)
Strong foundation in experimental design, hypothesis testing, regression modeling, and causal inference
Experience with ML algorithms relevant to ranking, prediction, and optimization problems: gradient boosted trees, deep learning, k-means, and related methods
Proven ability to extract actionable signals from noisy, high-volume datasets and communicate findings clearly
Track record of owning projects end-to-end, from problem framing through to production impact
Experience in mobile advertising, programmatic, or ad tech (strongly preferred)
Familiarity with mobile measurement and attribution or campaign performance optimization in mobile applications (strongly preferred)
Background working alongside ML engineering or product teams on systems where the model is the product (strongly preferred)
Advanced degree (Master's or PhD) in Statistics, Computer Science, Mathematics, or a related quantitative discipline (strongly preferred)
Paid leave programsPaid holidaysHealthcare, dental and vision insuranceDisability and life insuranceCommuter benefitsPhysical and financial wellness programsUnlimited discretionary time off (DTO) in the USReimbursement for mobile expensesFully stocked pantriesIn-office catered lunches 5 days per week
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