Build and maintain automated and dynamic predictive LTV models for mobile apps across multiple geographies, channels, campaigns, and platforms.
Develop automated revenue and user growth forecasting systems that integrate with UA and finance workflows.
Own the statistical framework for cohort modeling, retention projections, ROAS forecasting, and lifetime value prediction.
Lead measurement strategy in a privacy-centric ecosystem, including: SKAdNetwork (SKAN) configuration and model-based postback interpretation, Probabilistic attribution and MMM, Incrementality testing and causal inference, Funnel and cohort analysis across a complex landscape of iOS/Android/PC and Console
Build data pipelines and automated reporting that harmonize deterministic and probabilistic signals.
Collaborate with marketing, finance, and business teams to translate insights into actionable strategies by providing: Paid media performance insights, Budget planning and scenario modeling, both one off and automated, Creative testing analytics, Channel-level optimization recommendations
Build and maintain data pipelines and dashboards to monitor marketing KPIs and model outputs.
Present findings and recommendations to stakeholders in a clear and compelling way.
Stay informed on emerging trends and best practices in marketing analytics and data science.

Requirements

8+ years of experience in data science, analytics, or a related field, with deep expertise in mobile marketing, predictive revenue modeling, or mobile UA analytics.
Advanced degree (Master’s or PhD) in Statistics, Applied Mathematics, Economics, Computer Science, or another quantitative discipline.
Expert knowledge of: Cohort-based modeling and LTV prediction, Marketing measurement frameworks (SKAN, ATT, MMM, incrementality), Paid media platforms: Meta, Google, TikTok, DSPs, SANs, Probabilistic and deterministic attribution approaches, last-click attribution and alternatives
Experience deploying models and working with engineering teams to automate workflows.
Strong programming experience in Python (or R) and proficiency in SQL.
Hands-on experience with ML frameworks (TensorFlow, PyTorch, scikit-learn) and advanced statistical modeling techniques.
Hands-on experience with modern data and analytics tools, including BigQuery/Snowflake, Airflow/dbt, Tableau/Looker, and Python-based ML frameworks (scikit-learn, TensorFlow, PyTorch).
Expertise in data visualization and storytelling using Tableau, Power BI, Looker, or similar tools.
Demonstrated ability to solve complex problems independently and lead cross-functional initiatives.

Benefits

Medical, dental, vision, health savings account or health reimbursement account, healthcare spending accounts, dependent care spending accounts, life and AD&D insurance, disability insurance
401(k) with Company match, tuition reimbursement, charitable donation matching
Paid holidays and vacation, paid sick time, floating holidays, compassion and bereavement leaves, parental leave
Mental health & wellbeing programs, fitness programs, free and discounted games, and a variety of other voluntary benefit programs like supplemental life & disability, legal service, ID protection, rental insurance, and others
If the Company requires that you move geographic locations for the job, then you may also be eligible for relocation assistance.

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

predictive modelingcohort modelingLTV predictionstatistical modelingprogramming in PythonSQL proficiencymachine learning frameworksdata pipeline developmentdata visualizationforecasting systems

Soft Skills

problem solvingcross-functional leadershipcommunicationcollaborationdata storytelling

Certifications

Master’s degreePhD in StatisticsPhD in Applied MathematicsPhD in EconomicsPhD in Computer Science