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Data Science Team Lead at Renmoney. We are seeking a . Data Science Team Lead . with expertise in banking/fintech to lead a high-performing DS team. This position combines advanced ML knowledge, team leadership, and cross-functional collaboration to drive data-driven solutions in scorecard development, portfolio risk management, and model performance monitoring.. Key Responsibilities:. . . Advanced ML Development and Deployment:. . . . Build and refine ML models for credit scoring, fraud detection, marketing strategies, and customer behavior analytics. . . Manage AI initiatives, including integrating external AI services. . . Oversee the lifecycle of ML models, from concept to deployment, including quality assurance, recalibration, and performance monitoring. . . . . Team and Stakeholder Management:. . . . Lead and develop the DS team through hiring, training, and performance management. . . Collaborate with risk, collection, and business teams to align DS projects with organizational needs. . . Facilitate communication and prioritize tasks to meet stakeholder expectations. . . . . Process and Tool Optimization:. . . . Manage tools and processes such as Git, Jira, Confluence, and Agile workflows. . . Ensure data reliability and stability through collaboration with DWH teams and feature-store administration. . . Drive integration and optimization of new and existing data sources. . . . . Knowledge and Standards Management:. . . . Maintain comprehensive project documentation and implement best practices. . . Oversee knowledge-sharing initiatives, including Confluence updates, Git documentation, and internal training. . . Stay ahead of industry trends and methodologies, introducing innovative tools and processes. . . . . . Technical:. Python, SQL, ML techniques (regression, classification, boosting, NLP/LLM). . . Tools:. PowerBI, Excel, Tableau, Git, AWS (preferred), MLOps experience. . . Soft Skills:. Team leadership, excellent communication, agile expertise, and risk analytics experience (preferred). . . Language:. Fluent English. . Preferred Qualifications:. . Educational background in mathematics, machine learning, or statistics. . Proven experience in fintech and banking, particularly in emerging markets. . Experience with AI-tools. . Expertise in ML for text, speech, and behavioral analytics or dynamic models in the card business.. . Company Location: Russia.