Data Scientist
Role details
Job location
Tech stack
Job description
As a Senior Data Scientist, you will play a key role in supporting game growth by leveraging data to build innovative, player-centric solutions. You won't just analyze data; you will own the lifecycle of data products - from identifying a player pain point to deploying a production-level solution. Product Vision & Strategy: Partner with Product Managers and Stakeholders to identify high-value opportunities, helping to define the data science roadmap for the one of the world's biggest mobile games. End-to-End Ownership: Own the process of creating new data products, from initial inception and requirement gathering to technical design, productionalization, and monitoring. Player Insights: Analyze player behavior to understand how features impact the game economy, progression, social dynamics, and sentiment. Advanced Modeling: Design and implement A/B tests, forecasting, clustering, and ML models that don't just "predict," but provide actionable "decision intelligence." Technical Excellence: Provide technical expertise throughout the product life cycle, ensuring high quality, scalability, and efficiency in our Data & Insights team. Collaborative Delivery: Work across departments (Product Analytics, Engineering, LiveOps, Marketing) to ensure data solutions are integrated and driving real-world impact for our players.
Requirements
We want a creative, highly motivated individual who enjoys tackling ambiguous problems and "figuring it out" with practical, scalable solutions.
Product Mindset: Outstanding problem-solving skills with a "user-first" mentality. You can conceptualize player behavior and determine the best metrics to measure success, even when data is messy or non-existent. Technical Stack: Advanced proficiency in Python and SQL. Experience with BI tools (Looker) and visualization libraries (Plotly, etc.). Data Engineering Savvy: Experience with data transformation at scale using dbt and Airflow. Production Experience: Proven track record of deploying data products to production (on GCS, AWS, or Azure) and implementing monitoring/alerting to ensure service quality. Scientific Rigor: Strong background in statistics, A/B testing methodology, and applying ML/AI to improve business understanding. Communication: Ability to translate complex methodologies into clear "so-whats" for non-technical stakeholders and business users. Bonus Points
Gaming Passion: A deep love for F2P mobile games and an understanding of game loops/economies. Specialized Knowledge: Familiarity with causal inference, Bayesian statistics, or MLOps platforms. Deep Learning & GenAI: Hands-on experience with LLMs, predictions using Transformers, or other Deep Learning architectures applied to behavioral data or content generation.