Data Scientist

Almus is looking for a Data Scientist to join our Analytics team and build production-grade machine learning models that directly impact marketing and business performance.

You will work on end-to-end ML solutions, from data and features to deployment and monitoring, focusing on improving LTV prediction quality, optimizing ML-driven costs, and driving key metrics such as LTV, ROAS, retention, and CAC. This is an individual contributor role with strong ownership, close collaboration with Marketing, Product, and Data teams, and a clear focus on real business impact.

Apply to join Almus and take ownership of high-impact data initiatives!

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 registries)
• 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