toogeza - Lead Data Scientist
Requirements
• Bachelor’s or Master’s degree in Statistics, Mathematics, Computer Science,Economics, or a related quantitative field. • 5+ years of experience as a Senior Data Scientist role/Lead role, leading both analytical and data science domain work. • Strong SQL and Python skills; experience with large datasets, notebooks, reproducible analysis, and Git-based workflows. • Solid knowledge of ML, statistics, experimental design, A/B testing, holdout evaluation, and business KPI analysis. • Commercial experience with predictive modeling, classification, segmentation,forecasting, model evaluation, and business impact measurement. • Experience with churn, uplift, LTV, retention, campaign analytics, or user behaviormodeling is a strong advantage. • Strong analytical and problem-solving mindset; ability to find the story in the data:uncovering trends and explaining them in clear business terms. • Commercial Experience working with large datasets and distributed computing tools(BigQuery, Spark, Hive, or similar). • 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 predictivemodeling techniques. • Will be a plus: • Experience in gaming, gambling, fintech, e-commerce, subscription, or other user-behavior-driven products. • Experience with BI tools such as Tableau, Looker, or Power BI. • Product mindset: the ability to go beyond numbers and propose actionable solutionsthat 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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