Team Lead, Decision Science

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Renmoney

WebsiteLinkedInAll Job Openings

501 - 1000 employees

Founded 2012

💳 Fintech

👥 B2C

🏦 Banking

Fintech • B2C • Banking

Renmoney is a digital banking platform that offers financial solutions such as loans, savings, and payments to consumers in Nigeria. With over ten years of experience, the company specializes in providing convenient loans and high-interest savings options to under-banked individuals, facilitating easy access to financial services through its user-friendly app. Renmoney is licensed and regulated by the Central Bank of Nigeria and aims to empower users by making their money work harder for them while ensuring a seamless banking experience.

📋 Description

• 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.