Senior Data Scientist

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September 30

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toogeza

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Recruitment • HR Tech • B2B

Toogeza is a recruitment and consultancy firm based in Ukraine, specializing in finding talent and providing recruitment solutions for tech companies. They offer a range of services including recruiting, sourcing, selection, onboarding assistance, auditing and setting up HR processes, and recruitment process outsourcing. Toogeza acts as a partner, deeply integrating into the hiring process by offering market insights and helping create team structures. They provide versatile hiring services for various tech domains, markets, and roles. Their core values include talent, top quality, trust, and tenacity. They serve clients worldwide, helping them find suitable candidates for both technical and leadership roles across different industries and markets.

11 - 50 employees

🎯 Recruiter

👥 HR Tech

🤝 B2B

📋 Description

• Analyze large volumes of game and player data to identify patterns, trends, and dynamics, and turn them into clear business conclusions. • Translate findings into practical recommendations for product improvements, highlighting what works, what doesn’t, and what opportunities to explore. • Perform deep-dive investigations into performance anomalies or game features to explain what happened and why. • Design, build, and deploy ML models (e.g., churn prediction, LTV forecasting, revenue uplift, player segmentation) from experimentation to production. • Own the full ML lifecycle: feature engineering, model training, validation, monitoring, retraining, and continuous improvement. Ensure models are scalable, explainable, and integrated into real-time or batch decision-making systems. • Collaborate with engineering teams to ensure seamless data pipelines and efficient model serving in production environments. • Establish best practices for ML monitoring: track model drift, bias, performance degradation, and implement retraining strategies. • Develop robust statistical and causal inference analyses to identify drivers of user behavior. • Define and develop M/L models to resolve complex tasks of LTV, Churn Prediction, Revenue Forecasting etc. • Support development and testing of predictive models through A/B tests and other controlled experiments. • Communicate complex insights in a simple, compelling way to both technical and non-technical audiences. • Help define metrics for new products or features, expanding high-level requirements with your analytical thinking and product insights.

🎯 Requirements

• Bachelor’s or Master’s degree in Statistics, Mathematics, Computer Science, Economics, or a related quantitative field. • 3+ years of experience as a Data Scientist, preferably in the gaming or tech industry. • Strong analytical and problem-solving mindset; ability to find the story in the data: uncovering trends and explaining them in clear business terms. • Experience working with large datasets and distributed computing tools (BigQuery, Spark, Hive, or similar). • Strong hands-on experience with SQL for complex queries and data wrangling. • Solid data visualization skills (Tableau/Power BI, Python) • Advanced skills in Python for data analysis. • Solid understanding of experimental design and statistical testing (A/B testing, hypothesis testing, confidence intervals). • Familiarity with causal inference techniques (e.g., Propensity Score Matching, Instrumental Variables, Difference-in-Differences, uplift modeling), and predictive modeling techniques. • English B2+ • Will be a plus: Knowledge of the iGaming industry or understanding of slot game mechanics. • Will be a plus: Ability to look at games from players’ point of view. • Will be a plus: Product mindset: the ability to go beyond numbers and propose actionable solutions that make an impact.

🏖️ Benefits

• Work on meaningful data products and shape them with your vision. • 25 vacation days + 15 sick days + 1 birthday leave. • Budget for English classes. • Budget for health insurance. • Annual education & development budget. • Flexible, remote-friendly culture with a small, dedicated team.