Data Science Expert
On-siteWarsaw, Mazovia, Poland
Job Summary
Identify mathematical and statistical limitations in existing ML solutions and deliver provably correct, more efficient alternatives. Validate the correctness of scaled solutions by diagnosing where distributed execution or approximation invalidates prototype-level results, then redesign accordingly. Own the full lifecycle of improvements from research and prototyping through production deployment and impact measurement. Drive the evolution and scalability of personalization and recommendation systems to meet future business and technical requirements. Contribute to end-to-end data-driven research including problem definition, data collection, model development, evaluation, and deployment. Collaborate with cross-functional teams to deploy solutions quickly and effectively. Mentor Data Scientists and ML Engineers while serving as a technical reference on statistical and mathematical rigor.
Required Qualifications
- M.Sc or PhD in Computer Science, Mathematics, Statistics, Engineering or a related field
- 5+ years of relevant working experience, including significant production ML ownership
- Demonstrated experience taking statistically sophisticated models from prototype to production and operating them successfully under real-world business constraints
- Experience with neural network architectures, including the ability to diagnose, interpret and debug their behavior in probabilistic or decision-making contexts (e.g. Bayesian Neural Networks, Neural Linear models)
- Strong theoretical foundation in at least one of: Multi-Armed Bandits, Bayesian methods, online learning, recommendation systems, or related decision-making frameworks
- Strong understanding of experimentation, causal inference and statistical evaluation of online decision systems
- Strong hands-on Python engineering skills, with the ability to design, implement, review, and maintain production-quality code, leveraging modern AI coding assistants (e.g., Claude, Cursor) to improve productivity and code quality
- Proficiency in SQL
- Clear written and verbal communication - able to explain statistical reasoning to non-technical stakeholders
- Ability to operate autonomously and influence decisions across teams without direct authority
Desired Qualifications
- Experience with probabilistic programming frameworks (e.g. PyMC or Numpyro)
- Familiarity with MLOps tooling (experiment tracking, model serving, monitoring)
- Familiarity with approximate inference methods (variational inference, MCMC)
- Experience with PySpark
- Experience in the Mobile Gaming industry
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