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 ResponsibilitiesDesign, develop, and deploy machine learning models to productionImprove product and business decision-making through data-driven approachesBuild and evolve end-to-end ML pipelines (data → features → model → inference → monitoring)Drive measurable impact on key product and commercial metricsStandardize ML approaches within the team (best practices, documentation, reproducibility)Provide technical input to the architecture of analytics and ML infrastructureDevelop and deploy models that drive growth in LTV, ROAS, retention, and CACInfluence performance and lifecycle marketing strategyAct as a domain expert and collaborate closely with Marketing, Product, and Data Engineering teamsRequirements3+ years of experience as a Data Scientist / ML EngineerExperience working with mobile subscription-based productsStrong Python skills (production-level code)Solid knowledge of classical machine learning algorithms and practical experience applying themExperience with feature engineering, model evaluation, and bias–variance trade-offsHands-on experience with marketing models such as LTV, churn, cohort, and funnel modelingExperience with attribution, incrementality, and uplift modelingStrong SQL skills and experience working with analytical datasetsExperience with production ML systems and A/B testingEnglish level: Intermediate+Nice To HaveExperience with BigQueryMLOps experience (Docker, CI/CD, model registres)Experience working with performance marketing data (Meta, Google Ads, Adjust)Knowledge of causal inferenceExperience with AutoML and Bayesian modelsWe OfferExciting challenges and growth prospects together with an international companyHigh decision-making speed and diverse projectsFlexibility in approaches, no processes for the sake of processesEffective and friendly communication at any levelHighly competitive compensation package that recognizes your expertise and experience, Performance Review practice to exchange feedback and discuss terms of cooperationFlexible schedule, opportunity to work in a stylish and comfortable office or remotelyRespect for work-life balance (holidays, sick days - of course)Bright corporate events and gifts for employeesAdditional medical insuranceCompensation for specialized training and conference attendanceRestaurant lunches at the company's expense for those working in the office, endless supplies of delicious food all year round