Team Lead, Decision Science

Data Science Manager

We are looking for a Data Science Manager with a strong background in managing data-driven solutions to lead a high-performing DS team within the banking sector. This role combines ML expertise, team leadership, and cross‑functional communication, with a focus on scorecard development, model performance, and portfolio risk monitoring.

• Advanced ML‑modeling and data‑exploration: ensembles and AI‑algorithms, AI‑initiatives management, external AI‑services integration. Focus on models and solutions for credit, fraud, marketing, collection and contact strategies, text, speech and behavioral analytics, dynamic pricing and limits.
• Stakeholders' expectations management: communication with risk (portfolio) team, collection team, other business units on score‑modelling and backlog prioritization, task clarification.
• DS‑team management: recruitment, training, performance improvement, scrum‑servicing, task‑management. Improvement DS‑team communication with consumers and business needs understanding.
• Environment, process and tools management: git, Jira board, Confluence content, Agile rituals.
• ML‑data management: collaboration with DWH‑team; data‑availability, reliability and quality assessment; new / existent data‑sources integrations support and management, data‑flow stability control, feature‑store administration.
• ML‑model lifecycle management: from business needs identification to "sell", deployment and production‑test stage. ML‑models stability monitoring and quality control, reassessment and proactive quality improvement (re‑calibration / re‑building).
• Knowledge management:
  Maintain up‑to‑date project documentation, implement standards, control discipline and maintain actuality for Confluence descriptions, feature‑store meta‑data, git documentation, internal experience sharing and handover, new methodologies and tools review and implementation.