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Team Lead, Decision Science

Team Lead, Decision Science

RenmoneyLagos, LA, NG
30+ days ago
Job type
  • Quick Apply
Job description

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.

Responsibilities

  • 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 : colabration with DWH-team; data-availability, reliability and quality assessment; new / existent data-sources integrations support and management, data-flow stability control, feature-store administation.
  • 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.

Requirements

  • Demonstrated experience working in fintech or banking, especially within emerging markets.
  • Hands-on experience developing ML scoring models for text, speech, behavioral analytics, and dynamic modeling in card businesses.
  • Strong programming skills in Python and SQL for data analysis, modeling, and automation.
  • Proven experience with machine learning techniques, including :
  • Regression, classification, ranking, boosting
  • Graph-based models, neural networks, NLP, and large language models (LLMs)
  • Solid understanding and practical implementation of AI concepts and systems.
  • Familiarity with MLOps, including data pipelines, model deployment, and productionizing machine learning solutions.
  • Experience with cloud computing platforms, especially AWS (highly preferred).
  • Proficiency with BI and data visualization tools such as PowerBI, Excel, Tableau, or Grafana.
  • Prior exposure to risk management or analytics, particularly within the cards or payments space.
  • Strong grasp of Agile and Scrum methodologies in a data or engineering environment.
  • Excellent communication and presentation skills, with the ability to simplify complex data concepts for both technical and non-technical audiences.
  • Fluent in spoken English.
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    Science • Lagos, LA, NG