Senior Data Scientist, AI Web Game

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🕒 March 1

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Wolf Games

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11 - 50 employees

Wolf Games is a global team of creatives and technologists pioneering generative gaming and delivering players unprecedented control.

📋 Description

• Own, define, and guide the implementation of our data collection strategy and governance across all titles and platforms. • Design and specify a scalable, real-time pipeline for ingesting, processing, and analyzing gameplay and engagement events which will be built by the engineering team. • Build the models and specify the data platforms that translate raw player data into actionable insights for both humans (designers, producers) and machines (AI training and evaluation). • Design and own the company-wide experimentation frameworks that help us measure fun, engagement, and narrative effectiveness. • Partner with executive and creative leadership to identify trends in player behavior across distribution channels and surface strategic, high-level learnings that guide where and how we launch. • Shape how Wolf Games measures success — help us understand and act on the signals that capture what keeps players coming back. • Act as the strategic authority for all data systems, setting standards for code, tools, and infrastructure, and mentoring future team members as the team grows.

🎯 Requirements

• 10+ years of experience in data science, analytics, and machine learning, with a demonstrable track record of leading data science initiatives from concept to production. • At least 5+ years in gaming, media, or interactive entertainment is strongly preferred. • Deep expertise working across structured and unstructured data. • Proven experience designing and consulting on event taxonomies and leading behavioral analytics frameworks for digital experiences, ideally from scratch. • Expert-level, hands-on experience and strategic understanding of modern data architectures (e.g., real-time streaming with Kafka/Kinesis, data lakes/warehouses like Snowflake/BigQuery, feature stores, MLOps pipelines). • A proven track record of applying machine learning or AI techniques to production systems using real-world user data — for personalization, content recommendation, or automated content evaluation. • The ability to own the entire data lifecycle, from high-level architectural strategy down to implementation and iteration. • Curiosity about games, player psychology, and generative AI — and a desire to work at their intersection. • Exceptional quantitative and communication skills: you can influence technical and creative executives and drive better decisions with data-backed storytelling. • A true ownership and builder’s mindset: you’re excited to define best practices, select and implement tools, and help shape our long-term data and AI strategy from the ground up.