Lead Data Scientist

• 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.

• English B2+

• 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.

We are toogeza, a Ukrainian recruiting company that is focused on hiring talents and building teams for tech startups worldwide. People make a difference in the big game, we may help to find the right ones.

Currently, we are looking for a Lead Data Scientist for SpinLab.

Location: Remote
Job Type: Full-Time

As a Lead Data Scientist, you will combine hands-on expertise, technical leadership, and product thinking to drive the development of scalable ML solutions.

You will play a key role in:

• 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