Introduction:
At Huuuge Games we make top grossing mobile games that bring people together through fun and social mobile gaming.
Become a part of an exciting adventure bringing fun & truly social experiences 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 curious, driven individuals who aim to push boundaries and turn data into real business impact. We work closely with stakeholders across the company and deliver high-value projects using cutting-edge tools and techniques. If you love turning insight into action, we’d love to work with you.
How will you make an impact with us?
Partner with our product and business teams to design, build and deploy advanced data science solutions.
Take ownership of full DS/ML project cycles — from ideation and stakeholder alignment, to implementation and ongoing maintenance.
Design, build, and deploy robust statistical and machine learning models that help us understand and predict player behavior, optimize game features, and personalize user experiences.
Design methodology, build tools and promote data driven culture for experimentation, including A/B tests, to guide product development and decision-making.
Build forecasting models to support product, marketing and finance strategy with reliable forward-looking insights.
Communicate your findings clearly and effectively across both technical and non-technical audiences, using appropriate visualizations and business context.
Advocate for data science best practices across the organization, contributing to code reviews, mentoring, and the evolution of internal DS standards and tools.
Collaborate well across the data team to ensure scalable deployment and monitoring of models in production.
Requirements
This is the right job for you if you have:
4+ years of experience as a Data Scientist or ML Engineer, with hands-on experience applying machine learning and statistical techniques to real-world problems.
Education – Bachelor’s, Master’s or PhD degree in a relevant field, e.g. data science, computer science, mathematics, statistics, econometrics, physics, engineering or similar.
Strong theoretical and practical knowledge in statistical modeling, causal inference and experimental design
Strong practical knowledge of Machine Learning, and ability to build models that can be used in large scale production environments.
Solid experience with Python 3 and its data science stack (e.g. pandas, numpy, scikit-learn, statsmodels, etc.)
Experience designing and interpreting A/B tests and other controlled experiments.
Proven track record of delivering production-level code and working in version-controlled, peer-reviewed codebases.
Ability to write clean, well-documented, and testable code.
Strong communication skills and ability to work cross-functionally in a fast-paced environment.
Experience in collaborative environments and teamwork-oriented culture.
Surprise us with:
Experience with Bayesian methods and probabilistic programming libraries such as PyMC, TensorFlow Probability, or NumPyro.
Experience with ML Ops practices and tools, such as MLFlow, Airflow, or Databricks.
Experience in deploying ML models to production environments and supporting their lifecycle.
Passion for gaming or experience in the mobile gaming industry.
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