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Data Scientist (ML)
Мэтч & Сопровод
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Описание вакансии
Текст:
TL;DR
Data Scientist (ML) (Python, PyTorch, LightGBM): Building production ML systems for ads monetization, LTV prediction, and in-game personalization across a portfolio of mobile games with an accent on end-to-end model ownership and business-metric optimization. Focus on researching open monetization problems, developing predictive and personalization models, validating them through A/B tests, and deploying iterative solutions to production.
Location: Relocation support is provided to countries where has offices.
Company
develops and operates a portfolio of mobile games with billions of installs, using machine learning to optimize user acquisition, monetization, and personalization.
What you will do
- Research and develop ad monetization optimization systems, including floor pricing and ad load balancing.
- Build models to predict LTV and other key user metrics from large-scale behavioral data.
- Develop in-game personalization systems for difficulty and content management.
- Own models end to end, from problem framing and research through production deployment and post-launch iteration.
- Validate models with A/B tests in collaboration with the analytical team and bring successful solutions to production.
Requirements
- Experience with predictive modeling and deploying ML models to production.
- Strong Python skills and hands-on experience with the modern ML stack.
- Profound understanding of statistics and machine learning.
- Experience framing open problems, exploring data, building baselines, and iterating toward ML solutions.
- B2+ English and fluent Russian are required.
Nice to have
- Experience with reinforcement learning, recommender systems, ad tech, or mobile games.
Culture & Benefits
- Relocation support to countries where company offices are located.
- Performance bonuses and a competitive market salary.
- Equipment, private medical coverage, sports reimbursement, paid vacation, and sick days.
- English, Greek, and Polish online language classes.
- Education and professional development reimbursement.
- Regular company events and monthly Friday meetings.
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