Renmoney

Renmoney

Renmoney is a leading fintech company in Nigeria that offers personal and business loans, savings, investment products, and other banking services. They believe in making finance simple, useful, and accessible to everyone by leveraging data-driven insi...

Banks
251-1K
Founded 2012

Description

  • Lead advanced machine learning modeling and data exploration, including ensembles, AI algorithms, and external AI service integrations.
  • Own AI initiative management across use cases such as credit, fraud, marketing, collections, contact strategies, text, speech, behavioral analytics, dynamic pricing, and limits.
  • Manage stakeholder expectations with risk, collections, and other business teams on score modeling, backlog prioritization, and task clarification.
  • Recruit, train, and support performance improvement for the data science team while managing Scrum-based task execution.
  • Improve team communication with internal consumers and ensure alignment with business needs.
  • Manage the operating environment and processes, including Git, Jira, Confluence, and Agile rituals.
  • Collaborate with the DWH team to assess data availability, reliability, and quality, and support new and existing data-source integrations.
  • Oversee feature store administration and control data-flow stability for ML systems.
  • Manage the ML model lifecycle from business need identification through deployment, production testing, and release.
  • Monitor model stability and quality, and drive recalibration or rebuilds when needed.
  • Maintain project documentation, internal knowledge sharing, standards, handover materials, and reviews of new methodologies and tools.

Requirements

  • Demonstrated experience 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 such as 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, is highly preferred.
  • Proficiency with BI and data visualization tools such as PowerBI, Excel, Tableau, or Grafana.
  • Prior exposure to risk management or analytics, particularly in the cards or payments space.
  • Strong grasp of Agile and Scrum methodologies in a data or engineering environment.
  • Excellent communication and presentation skills for both technical and non-technical audiences.
  • Fluent spoken English.

Interested in this position?

Apply directly on the company website

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