Team Lead, Decision Science

About the role

renmoney is seeking a Data Science Manager to lead a high‑performing Decision Science team within the banking sector. The role blends advanced machine‑learning expertise, team leadership, and cross‑functional communication to drive credit scoring, fraud detection, and portfolio risk monitoring.

Key responsibilities

• Design and implement advanced ML models (ensembles, AI algorithms) for credit, fraud, marketing, collections, and dynamic pricing.
• Manage stakeholder expectations across risk, collection, and business units, prioritising backlogs and clarifying tasks.
• Recruit, train, and coach the DS team; oversee scrum ceremonies and task management.
• Maintain the data‑science environment using Git, Jira, Confluence, and Agile rituals.
• Collaborate with the DWH team to ensure data availability, quality, and feature‑store administration.
• Oversee the full ML model lifecycle from business need identification to deployment, monitoring, and continuous improvement.
• Document projects, enforce standards, and share knowledge across the organisation.

Required profile

• Proven experience in fintech or banking, especially in emerging markets.
• Hands‑on experience building ML scoring models for text, speech, behavioural analytics, and dynamic card‑business modelling.
• Strong programming background in Python and SQL.
• Familiarity with MLOps, data pipelines, and production‑grade model deployment.
• Experience with cloud platforms, preferably AWS.
• Exposure to risk management or analytics in cards or payments.

Required skills

• Python
• SQL
• Regression, classification, ranking, boosting
• Graph‑based models, neural networks, NLP, large language models (LLMs)
• MLOps
• AWS
• PowerBI, Excel, Tableau, Grafana
• Git, Jira, Confluence