Data Scientist - Marketing & Product

Scopely • San Francisco, CA

6d • $203,000 - $290,000

About The Position

Scopely is a global gaming company whose mission is to inspire play every day. Niantic (a division of Scopely) inspires people to explore the world together through products that promote exercise, exploration, and real-world social interaction. We’re seeking a strategic, impact-driven Staff Data Scientist to partner with Marketing and Product. You will lead scalable measurement frameworks, predictive models, and AI-powered analytics to shape user acquisition, engagement, monetization, and long-term player value. As a senior IC, you’ll define data strategy across marketing and product analytics, elevate experimentation and causal inference, and leverage modern AI tools to accelerate insights and decision-making. You’ll collaborate with Marketing, Product, Engineering, Finance, and Executive Leadership to drive measurable business outcomes.

Requirements

• 7+ years in data science supporting Marketing, Growth, UA, or Product Analytics (gaming/mobile preferred).
• Proven experience building production-grade predictive models (LTV, churn, propensity, MMM) that drive impact.
• Strong expertise in experimentation, causal inference, and marketing measurement.
• Advanced SQL and Python skills, including scalable ETL and production workflows.
• Experience with BI tools (e.g., Looker) and enabling self-serve analytics.
• Ability to influence senior stakeholders and drive executive-level adoption.

Nice To Haves

• End-to-end delivery experience (telemetry, QA, ETL, modeling, deployment, dashboards).
• Experience with large-scale datasets.
• Familiarity with BigQuery, Composer, and Airflow.

Responsibilities

• Marketing & Product Analytics Design scalable measurement frameworks across acquisition, retention, monetization, and lifecycle marketing.
• Build and productionize advanced models (LTV, churn, propensity, incrementality, MMM) to inform investment and roadmap decisions.
• Partner with Marketing and Finance to optimize budget allocation and ROI.
• Experimentation & Causal Inference Raise experimentation standards (A/B testing, quasi-experimental methods, incrementality).
• Translate privacy-constrained attribution environments (e.g., SKAdNetwork, aggregated reporting) into actionable insights.
• Data Engineering & Infrastructure Architect and maintain scalable ETL pipelines for marketing and product data (e.g., Airflow, Composer).
• Design optimized data models and warehouse schemas for high-performance analytics.
• Build reusable data assets, feature stores, and modular analytics frameworks.
• AI-Driven Analytics Apply modern AI/ML tools (LLMs, coding assistants, automated workflows) to accelerate modeling and analysis.
• Integrate AI into analytics workflows to improve speed, quality, and reproducibility.
• Promote technical excellence and responsible AI adoption.

Benefits

• employees may be eligible for equity, bonuses, and a comprehensive benefits package, including healthcare benefits, retirement benefits, pet insurance, paid holidays, paid Scopely free days, and unlimited paid time off

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: No Education Listed