Renmoney

Fintech offering loans, savings, and investments

Team Lead – Decision Science

Applied Machine LearningConfirmed live in the last 24 hours

Full-timeLagos, NigeriaNo salary listedRemote

About the Job

Requirements

Demonstrated experience working in fintech or banking, especially within emerging markets.
Hands-on experience developing machine-learning 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.
Experience with regression, classification, ranking, boosting, graph-based models, neural networks, natural language processing, and large language models.
Solid understanding and practical implementation of artificial intelligence concepts and systems.
Familiarity with MLOps, including data pipelines, model deployment, and productionizing machine-learning solutions.
Proficiency with business intelligence and data visualization tools such as Power BI, 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 technical and non-technical audiences.
Fluency in spoken English.

Responsibilities

Develop advanced machine-learning models and explore data using ensembles and artificial-intelligence algorithms; manage artificial-intelligence initiatives and integrate external artificial-intelligence services for credit, fraud, marketing, collection and contact strategies, text, speech and behavioral analytics, dynamic pricing, and limits.
Manage stakeholder expectations by communicating with risk portfolio teams, collection teams, and other business units on score modeling, backlog prioritization, and task clarification.
Manage the data science team, including recruitment, training, performance improvement, scrum servicing, and task management; improve communication between the team and consumers and its understanding of business needs.
Manage the environment, processes, and tools, including Git, Jira boards, Confluence content, and Agile rituals.
Manage machine-learning data in collaboration with the data warehouse team, assess data availability, reliability, and quality, support and manage new and existing data-source integrations, control data-flow stability, and administer the feature store.
Manage the machine-learning model lifecycle from identifying business needs through deployment and production testing; monitor model stability and quality, reassess models, and proactively improve quality through recalibration or rebuilding.
Maintain up-to-date project documentation, implement standards, control discipline, keep Confluence descriptions, feature-store metadata, and Git documentation current, share internal experience and handovers, and review and implement new methodologies and tools.

Desired Qualifications

Experience with cloud computing platforms, especially Amazon Web Services.

Team Lead, Decision Science

Renmoney · Lagos, Nigeria (Remote) · Full-time · Posted 2025-04-10

Workplace: remote

Department: Decision Science

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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About the Company

Renmoney

Fintech offering loans, savings, and investments

Renmoney provides personal and business financial products, including loans, savings, and investments, designed to be simple, useful, and accessible. It uses data-driven insights to understand customers and tailor offerings to individual needs, enabling convenient loans to help people do more today, savings plans to stay on track with goals, and investments to grow money over time. The company differentiates itself by focusing on making finance easy and available to a broad audience, rather than restricting access, and by combining a flexible hybrid work model with customer-centric product design. Its goal is to help people manage money more effectively and reach their financial objectives.

Company size: 501-1,000
Company stage: Not listed
Total funding: Not listed
Headquarters: Lagos, Nigeria
Founded: 2012

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