toogeza - Lead Data Scientist
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Requirements
• Bachelor’s or Master’s degree in Statistics, Mathematics, Computer Science, Economics, or a related quantitative field. • 5+ 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. • Will be a plus: • Knowledge of the iGaming industry or understanding of slot game mechanics • Ability to look at games from players' point of view • Product mindset: the ability to go beyond numbers and propose actionable solutions that make an impact.
Responsibilities
• Ensuring what we build drives business value • Defining how we build (processes, standards, scalability, performance) • This role requires close collaboration with product and business stakeholders to translate complex problems into practical, high-impact solutions. • Work closely with product and business teams to: • Translate business problems into data science solutions or data analytics researches • Define clear success metrics and KPIs • Turn insights into actionable recommendations that impact revenue and player behavior • Ensure all models and analyses are aligned with real business outcomes, not just technical performance • Design, build, and deploy ML models (e.g., churn prediction, LTV forecasting, revenue uplift, player segmentation) from experimentation to production. • Define and implement standardized, scalable DS/DA processes across the team: • Model development lifecycle (design → validation → production) • Code quality, documentation, and reproducibility • Experimentation and evaluation frameworks • Continuously improve delivery efficiency, reducing time from idea → production • Identify opportunities to automate manual analytical workflows using AI/ML
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. • Remote-friendly culture with a small, dedicated team. • If this role sounds like a fit — we’d love to hear from you! Just send over your CV and anything else you’d like us to consider.
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