Data Scientist

Almus is seeking a Data Scientist to join the Analytics team and develop production-grade machine learning models that directly impact marketing and business performance. You will work on end-to-end ML solutions focusing on LTV prediction, cost optimization, and driving key metrics like ROAS, retention, and CAC with strong business impact.

• Design, develop, and deploy machine learning models to production environments
• Build and evolve end-to-end ML pipelines including data, features, model, inference, and monitoring
• Drive measurable impact on key product and commercial metrics
• Standardize ML approaches within the team through best practices, documentation, and reproducibility
• Provide technical input to analytics and ML infrastructure architecture
• Develop models that drive growth in LTV, ROAS, retention, and CAC
• Influence performance and lifecycle marketing strategy
• Collaborate closely with Marketing, Product, and Data Engineering teams as a domain expert

• 3+ years of experience as a Data Scientist or ML Engineer
• Experience working with mobile subscription-based products
• Strong production-level Python skills
• Solid knowledge of classical machine learning algorithms
• Practical experience with feature engineering, model evaluation, and bias-variance trade-offs
• Hands-on experience with marketing models: LTV, churn, cohort, and funnel modeling
• Experience with attribution, incrementality, and uplift modeling
• Strong SQL skills and analytical dataset experience
• Experience with production ML systems and A/B testing
• Intermediate+ English level
• Nice to have: BigQuery, MLOps (Docker, CI/CD, model registries), performance marketing data (Meta, Google Ads, Adjust), causal inference, AutoML, Bayesian models

Work Environment: Flexible schedule with options for stylish office workspace or remote work

Benefits:

• Highly competitive compensation package
• Performance review practice for feedback and cooperation discussion
• Respect for work-life balance including holidays and sick days
• Additional medical insurance
• Compensation for specialized training and conference attendance
• Restaurant lunches at company expense for office workers
• Endless food supplies throughout the year
• Bright corporate events and employee gifts

Work Culture: High decision-making speed, diverse projects, flexible approaches, effective and friendly communication at all levels