Дата аналитик

TBC Uzbekistan is a digital financial services ecosystem that provides digital banking, payment solutions, credit installments, retail platforms for SMEs, and digital insurance services to millions of users.

• Define and drive the company's commercial Machine Learning strategy;
• Lead the development, deployment, and maintenance of ML models aimed at increasing revenue and customer value;
• Build and enhance models for personalization, recommendation systems, Next Best Action (NBA), Next Best Offer (NBO), response prediction, churn prediction, propensity scoring, cross-sell, and up-sell;
• Partner with CVM, Marketing, and Product teams to prioritize ML initiatives and translate business challenges into scalable ML solutions;
• Own the full ML lifecycle—from research and experimentation to production deployment, performance monitoring, and continuous model retraining;
• Manage the ML backlog, assess business impact, and prioritize initiatives based on value and strategic importance;
• Define and implement frameworks for measuring model performance and business impact;
• Collaborate with engineering teams to develop and improve MLOps capabilities, ensuring reliability, scalability, reproducibility, and operational excellence of ML solutions;
• Deliver measurable commercial impact through data-driven machine learning solutions.

• 7+ Years of experience in Machine Learning or Data Science, including at least 2–3 years leading ML or Data Science teams;
• Proven experience designing, developing, and deploying ML models that directly improve commercial or business performance;
• Hands-on experience with recommendation systems, personalization, propensity modeling, churn prediction, customer segmentation, uplift modeling, or similar commercial ML use cases;
• Strong understanding of modern machine learning algorithms, model evaluation techniques, and feature engineering best practices;
• Excellent Python skills and hands-on experience with major ML frameworks such as scikit-learn, XGBoost, LightGBM, CatBoost, TensorFlow, and/or PyTorch;
• Strong SQL skills and experience working with large-scale datasets;
• Experience building production-grade ML systems and solid understanding of MLOps practices, including CI/CD, model versioning, monitoring, and model registries;
• Strong ability to translate business objectives into technical solutions and estimate expected business impact;
• Demonstrated experience leading teams, mentoring data scientists, and collaborating with cross-functional stakeholders;
• English proficiency sufficient for reading technical documentation and collaborating with international teams;
• Nice to have: Experience in banking, fintech, telecommunications, or e-commerce serving millions of customers, Hands-on experience implementing Recommendation Systems, Reinforcement Learning, or Generative AI for commercial applications, Experience building real-time inference systems and event-driven architectures, Understanding of ML product economics, model ROI evaluation, and value measurement, Experience defining ML strategy and building a Machine Learning function from the ground up, Experience with cloud platforms and distributed computing frameworks.

• Medical insurance with extended coverage after the probation period;
• Coverage for conference participation;
• Discounts for English language courses and access to educational platforms;
• Internal meetups;
• Class “A” office in the city center;
• Team-building and sports events.