Introduction:
At Huuuge Games we make top-grossing mobile games that bring people together through fun and social experiences.
Become part of an exciting adventure, bringing joy to millions of players around the world from one of our offices in Poland.
We are an in-office-first company and operate in a hybrid model (3 days from the office).
Join our exceptional Data Science team - a group of highly skilled, curious, and driven individuals who work with leading edge tools, shape best practices, and transform data into real business impact. As a Senior Data Scientist, you’ll enjoy significant autonomy, working on some of the most interesting challenges in mobile gaming - from player behavior modeling to building large-scale personalization systems.
How will you make an impact with us?
Lead the design, development, and deployment of advanced data science solutions that drive measurable business impact.
Build and productionize machine learning models for improving player engagement and monetization.
Design methodology and develop tooling for the experimentation at scale to support data-driven decision-making.
Implement and promote state-of-the-art methods in causal inference, statistical modelling and model validation.
Collaborate closely with cross-functional teams (including Product, Marketing, and Engineering) to deliver end-to-end solutions.
Shape technical standards and help build scalable internal tools.
Ensure high-quality, maintainable, and well-documented code in a collaborative environment.
Champion best practices in Data&AI across the company through professional communication, education, and innovation.
This is the right job for you if you have:
5+ years of experience in Data Science or Machine Learning, ideally in product-oriented and highly data-driven environments.
Proven track record of end-to-end ownership of ML or analytics projects - from concept to production.
Strong theoretical and practical knowledge in statistics, machine learning, and experimental design.
Deep hands-on experience with Python (pandas, numpy, scikit-learn, TensorFlow/PyTorch, statsmodels).
Proficiency in SQL and experience with PySpark or other big data tools.
Familiarity with Cloud Infrastructure, ML Ops and deployment practices (for example Databricks, MLFlow, Github Actions).
Ability to communicate complex insights clearly to non-technical audiences.
A proactive, ownership-driven mindset and ability to thrive in a dynamic, fast-paced environment.
Surprise us with:
Extensive practical experience in Product Data Science, with a strong focus on experimentation methodologies, causal inference and data-driven product decision-making.
Experience building scalable, production-level data science solutions using best practices from software engineering.
Experience with Bayesian modeling and probabilistic programming (PyMC, TFP, NumPyro).
Passion for mobile games, understanding player behavior, and modeling game economy.
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