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Senior Data Scientist – Production ML
Not specifiedFull-timeData ScienceMobile Gaming
Join a data and AI team developing scalable personalization and recommendation systems for a global mobile gaming business. The role combines applied research with end-to-end production ownership, focusing on reinforcement learning, Bayesian methods, and statistical decision systems.
Responsibilities
- Identify mathematical and statistical limitations in existing machine learning solutions and develop more efficient, provably correct alternatives.
- Validate scaled solutions by diagnosing the effects of distributed execution and approximation, then redesigning systems where needed.
- Own improvements from research and prototyping through production deployment and impact measurement.
- Advance the scalability of personalization and recommendation systems.
- Lead end-to-end data-driven research, including problem definition, data collection, model development, evaluation, and deployment.
- Collaborate with engineering, BI, and product teams to deploy solutions effectively.
- Mentor data scientists and machine learning engineers and provide technical guidance on statistical and mathematical rigor.
Requirements
- Master’s or PhD in computer science, mathematics, statistics, engineering, or a related field.
- At least 5 years of relevant experience, including substantial ownership of production machine learning systems.
- Demonstrated ability to move statistically sophisticated models from prototypes into reliable production systems.
- Experience with neural network architectures and diagnosing, interpreting, and debugging their behavior in probabilistic or decision-making contexts.
- Strong theoretical knowledge 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.
- Advanced Python engineering skills for designing, implementing, reviewing, and maintaining production-quality code.
- Proficiency in SQL.
- Clear written and verbal communication, including the ability to explain statistical reasoning to nontechnical stakeholders.
- Ability to work autonomously and influence cross-functional decisions without direct authority.
Nice to have
- Experience with probabilistic programming frameworks such as PyMC or NumPyro.
- Familiarity with MLOps tools for experiment tracking, model serving, and monitoring.
- Knowledge of approximate inference methods such as variational inference or MCMC.
- Experience with PySpark.
- Experience in the mobile gaming industry.