Senior Data Scientist

We’re looking for a Senior Data Scientist to help shape and expand the analytics backbone of our games ecosystem. This role is both deeply technical and highly collaborative—you’ll work across teams and disciplines to transform complex data into actionable insights that drive product innovation, player engagement, and business growth.

The ideal candidate will have a solid quantitative background, specifically including a mature understanding of statistics, logic, measurement theory, linear algebra and practical, demonstrated experience in modeling and machine learning. Further, strong analytical and problem-solving and troubleshooting skills are required; fluency in coding, algorithms, and systems design; clean and effective communication skills; genuine interest in solving complex problems. A resilience against failure and constructive criticism to iterate through difficult problems efficiently.

You’ll thrive here if you combine strong quantitative expertise with a curious, problem-solving mindset, the ability to work in ambiguous, evolving contexts, and the determination to own projects end to end, from research to real-world impact. You will play a crucial role in scaling data science products that have a direct impact on the success of High 5 Games!

What You’ll Do

• Design, implement, and maintain robust data pipelines, from event generation through ETL to clean, intelligent storage.
• Retrieve, process, and integrate data using APIs and webhooks, ensuring quality, accuracy, and integrity at every step.
• Develop reporting layers—dashboards, automated reports, and notifications—to deliver insights across teams.
• Curate raw data into meaningful structures for CRM, product, and monetization teams.
• Build predictive and optimization models for areas like player lifetime value, churn prediction, monetization strategies, and game recommendations.
• Define and execute multivariate testing frameworks to optimize product and campaign performance.
• Explore and apply state-of-the-art AI and ML techniques, in real-time processes, proposing innovative approaches for real-world challenges.
• Partner and influence cross-functional teams—including CRM, Server, Data Engineering, and Leadership—to implement end-to-end solutions quickly and effectively.
• Align data projects with business goals and ROI considerations, applying pragmatic 80/20 thinking to maximize impact.
• Deeply understand and navigate the abstract mechanics of our ecosystem—game economies, monetization levers, RTPs, and more.

Requirements:

• Master's Degree in a quantitative field
• Programming experience in a scripting language such as Python or R
• Fundamental understanding of statistics and machine learning models
• Knowledge of statistical testing, data visualization best practices, and data mining
• Familiarity with cloud computing environments and their components (at least one among AWS, GCP, Azure etc)
• Proficiency in SQL
• Strong problem-solving skills
• Resilience against difficult tasks
• Solid and effective English communication skills
• Attention to detail and ingrained affinity for sanity checks and clean delivery

Nice to have:

• PhD degree in a quantitative field or 4+ years of professional experience in a relevant field (technology/gaming/algorithms/research…)
• Experience working with GCP tech stack
• A good understanding of database design and management
• Experience in developing and applying machine learning algorithms to business problems
• Experience in Java and/or C++
• Experience in AI productionisation  and Agentic deployment

- Master's Degree in a quantitative field (PhD preferred, or 4+ years professional experience) - Programming experience in Python or R - Fundamental understanding of statistics and machine learning models - Knowledge of statistical testing, data visualization, and data mining - Familiarity with cloud computing environments (AWS, GCP, Azure) - Proficiency in SQL - Strong problem-solving skills and resilience - Effective English communication skills - Attention to detail and affinity for sanity checks