Data Science and Analytics Lead

We represent a technology player whose digital banking platform is transforming financial services in emerging markets, making a real impact by embedding credit and savings products into the digital channels people use every day. Their data-driven technology powers MNOs, fintechs, and banks, enabling them to scale fast and drive financial inclusion for millions. For those looking to work on cutting-edge financial tech, with real-world impact, this is the opportunity for you. With rapid growth, industry recognition, and a team that thrives on innovation, this is a chance to shape the future of finance in high-growth markets across Africa.

Job Description :

The Data Science and Analytics Lead will enhance their credit risk modelling, predictive analytics, and operational efficiency. Improve multi-source data integration, strengthening model governance, automating data processes, and scaling our infrastructure for faster decision-making and market expansion. The Data Science and Analytics Lead will drive data-driven insights, refine risk models, and build scalable solutions that optimize lending decisions and business growth.

Your daily adventures include :

Strategic Leadership & Business Impact

• Drive the development and execution of the data science strategy to support business growth, embedded finance, and new market expansion
• Leverage AI and behavioral science insights to enhance credit performance, customer engagement, and savings adoption.
• Partner with product, risk, and engineering teams to integrate data science into decision-making and operational processes
• Build, refine, and deploy AI-powered credit scoring models, ensuring high performance, fairness, and explainability.
• Lead experimentation and A / B testing initiatives to enhance underwriting, portfolio management, and product innovation.

Data Infrastructure & Scalability

• Collaborate with Engineering to expand data science capabilities to support multiple markets, optimizing for scalability and adaptability
• Ensure data integrity, security, and compliance across all data science initiatives
• Drive best practices in model development, MLOps, and responsible AI
• Promote cross-functional collaboration to maximize the value of data science across the organization.

Requirements

What it takes to succeed :

• Strong background in data science, machine learning, and AI, with experience in credit risk modelling and financial services
• Deep understanding of AI governance, model transparency, and regulatory compliance in financial services
• Hands-on experience with MLOps, model deployment, and automated monitoring solutions
• Strong analytical mindset with a proven ability to drive business impact through data science
• Excellent leadership skills, with the ability to mentor and build high-performing teams
• Bachelor's degree in a quantitative field such as Statistics, Mathematics, Physics, Computer Science, Data Science, Engineering, Economics, Financial Engineering, Actuarial Science or a related discipline
• Experience in fintech, digital lending, or embedded finance is preferred
• Exposure to cloud platforms such as AWS, GCP, or Azure for data engineering and machine learning is beneficial
• Familiarity with graph analytics, network science, or behavioral data modelling is beneficial
• Knowledge of causal inference techniques and advanced experimentation methodologies is beneficial
• Prior experience in expanding data science functions into new markets is beneficial