Data Scientist

Key Responsibilities:

• Design, develop, and deploy machine learning models to production

• Improve product and business decision-making through data-driven approaches

• Build and evolve end-to-end ML pipelines (data → features → model → inference → monitoring)

• Drive measurable impact on key product and commercial metrics

• Standardize ML approaches within the team (best practices, documentation, reproducibility)

• Provide technical input to the architecture of analytics and ML infrastructure

• Develop and deploy models that drive growth in LTV, ROAS, retention, and CAC

• Influence performance and lifecycle marketing strategy

• Act as a domain expert and collaborate closely with Marketing, Product, and Data Engineering teams

Requirements:

• 3+ years of experience as a Data Scientist / ML Engineer

• Experience working with mobile subscription-based products

• Strong Python skills (production-level code)

• Solid knowledge of classical machine learning algorithms and practical experience applying them

• Experience with feature engineering, model evaluation, and bias–variance trade-offs

• Hands-on experience with marketing models such as LTV, churn, cohort, and funnel modeling

• Experience with attribution, incrementality, and uplift modeling

• Strong SQL skills and experience working with analytical datasets

• Experience with production ML systems and A/B testing

• English level: Intermediate+

Nice to have:

• Experience with BigQuery

• MLOps experience (Docker, CI/CD, model registres)

• Experience working with performance marketing data (Meta, Google Ads, Adjust)

• Knowledge of causal inference

• Experience with AutoML and Bayesian models

We Offer:

• Exciting challenges and growth prospects together with an international company

• High decision-making speed and diverse projects

• Flexibility in approaches, no processes for the sake of processes

• Effective and friendly communication at any level

• Highly competitive compensation package that recognizes your expertise and experience, Performance Review practice to exchange feedback and discuss terms of cooperation

• Flexible schedule, opportunity to work in a stylish and comfortable office or remotely

• Respect for work-life balance (holidays, sick days - of course)

• Bright corporate events and gifts for employees

• Additional medical insurance

• Compensation for specialized training and conference attendance

• Restaurant lunches at the company's expense for those working in the office, endless supplies of delicious food all year round