Senior Data Scientist

<p><strong><span>Introduction:</span></strong></p><p></p><p><span>At Huuuge Games we make top-grossing mobile games that bring people together through fun and social experiences.</span></p><p><span>Become part of an exciting adventure, bringing joy to millions of players around the world from one of our offices in Poland.<br/>We are an in-office-first company and operate in a hybrid model (3 days from the office).</span></p><p><span>Join our exceptional </span><strong><span>Data Science team</span></strong><span> - 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 </span><strong><span>Senior Data Scientist</span></strong><span>, 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.</span></p><p></p><p><strong><span>How will you make an impact with us? </span></strong></p><p></p><ul><li><p><span>Lead the design, development, and deployment of advanced data science solutions that drive measurable business impact.</span></p></li><li><p><span>Build and productionize machine learning models for improving player engagement and monetization.</span></p></li><li><p><span>Design methodology and develop tooling for the experimentation at scale to support data-driven decision-making.</span></p></li><li><p><span>Implement and promote state-of-the-art methods in causal inference, statistical modelling and model validation.</span></p></li><li><p><span>Collaborate closely with cross-functional teams (including Product, Marketing, and Engineering) to deliver end-to-end solutions.</span></p></li><li><p><span>Shape technical standards and help build scalable internal tools.</span></p></li><li><p><span>Ensure high-quality, maintainable, and well-documented code in a collaborative environment.</span></p></li><li><p><span>Champion best practices in Data&amp;AI across the company through professional communication, education, and innovation.</span></p></li></ul> <h3>Requirements</h3> <p><strong><span>This is the right job for you if you have:</span></strong></p><p></p><ul><li><p><strong><span>5+ years</span></strong><span> of experience in Data Science or Machine Learning, ideally in product-oriented and highly data-driven environments.</span></p></li><li><p><span>Proven track record of end-to-end ownership of ML or analytics projects - from concept to production.</span></p></li><li><p><span>Strong theoretical and practical knowledge in statistics, machine learning, and experimental design.</span></p></li><li><p><span>Deep hands-on experience with </span><strong><span>Python</span></strong><span> (pandas, numpy, scikit-learn, TensorFlow/PyTorch, statsmodels).</span></p></li><li><p><span>Proficiency in </span><strong><span>SQL</span></strong><span> and experience with </span><strong><span>PySpark</span></strong><span> or other big data tools.</span></p></li><li><p><span>Familiarity with Cloud Infrastructure, ML Ops and deployment practices (for example Databricks, MLFlow, Github Actions).</span></p></li><li><p><span>Ability to communicate complex insights clearly to non-technical audiences.</span></p></li><li><p><span>A proactive, ownership-driven mindset and ability to thrive in a dynamic, fast-paced environment.</span></p></li></ul><p></p><p><strong><span>Surprise us with:</span></strong></p><p></p><ul><li><p><span>Extensive practical experience in Product Data Science, with a strong focus on experimentation methodologies, causal inference and data-driven product decision-making.</span></p></li><li><p><span>Experience building scalable, production-level data science solutions using best practices from software engineering.</span></p></li><li><p><span>Experience with Bayesian modeling and probabilistic programming (PyMC, TFP, NumPyro).</span></p></li><li><p><span>Passion for mobile games, understanding player behavior, and modeling game economy.</span></p></li></ul><p></p><p><strong><span>We thought you’d appreciate:</span></strong></p>