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Senior Data Scientist – Production ML

Playtika·Израиль·en
Не указаноПолная занятостьData 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.

Обязанности

  • 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.

Требования

  • 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.

Будет плюсом

  • 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.

Соответствие

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