This role owns the Analytics function end-to-end and combines strategic leadership with hands-on analytical work. From data quality and experimentation design to insight translation and the impact of decisions on existing products and the development of new ones.
Analytics Lead
Key Responsibilities:
- Lead and develop the Analytics team, ensuring high performance, clear ownership, and consistent delivery
- Actively drive data discovery, experimentation, and A/B testing
- Personally contribute to and review complex analytics work, ensure high standards of data quality, analytical correctness, and code quality across all analytics work
- Define analytics priorities and contribute to planning in collaboration with Product Managers & Project Managers
- Continuously improve analytics tools and processes, combining hands-on problem solving with building scalable, repeatable solutions to increase impact and efficiency
- Collaborate closely with Product Managers, ML Engineers, and Data Engineers across the full product lifecycle
Requirements:
- 5+ years of experience in data/product analytics, or applied data science
- At least 1 year of experience leading an analytics team
- Strong, hands-on experience in igaming domain
- Proven ability to take ownership of analytics outcomes and influence decisions
- Ability to explain complex analytical findings to non-technical audiences
- Strong SQL skills and experience working with large datasets
- Solid knowledge of statistics, hypothesis testing, and experimental design. Hands-on experience running and analyzing A/B tests
- Strong proficiency in Python for analytics (pandas, numpy, scipy)
- Strong skills in data discovery and exploratory analysis
- Experience with Tableau or other BI tools
- Ability to build dashboards that clearly explain product and player performance
Nice to have:
- Practical experience building models, including clustering and prediction models
- Familiarity with libraries such as scikit-learn, XGBoost, LightGBM, PyTorch, etc.
- Understanding of model evaluation and validation
- Translating ML insights into actionable recommendations
Interview process:
- Intro Interview (30 mins)
- Technical Interview (60 mins)
- Leadership Interview (60 mins)
- Introduction with CEO (30 mins)
Benefits:
- 21 day of paid vacation per year
- Education budget of $600 per year provided
- Medical Insurance
- Professional English courses
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