Data Science and Analytics Lead
Data Science and Analytics Lead
Nairobi, Dubai, Portugal
Credable is transforming financial services in emerging markets with its best-in-class Digital Banking Platform. We help partners launch financial products by embedding them into digital channels their customers already use.
The result is a win-win-win for partners, customers, and Credable. Having deployed across multiple markets in Africa, we’ve proven our platform meets a critical need and is driving us toward our core objectives:
- Democratizing financial services by reaching over 500 million people.
- Becoming the most trusted source of data in emerging markets.
The Role
Credable leverages telco, banking, and other alternative data to build credit models for the underbanked. We seek to enhance our credit risk modeling, predictive analytics, and operational efficiency.
Key gaps include improving multi-source data integration, strengthening model governance, automating data processes, and scaling our infrastructure for faster decision-making and market expansion. We need a leader to drive data-driven insights, refine risk models, and build scalable solutions that optimize lending decisions and business growth.
The Data Science and Analytics team is pivotal to driving our fintech’s growth and efficiency. Our roadmap focuses on enhancing credit risk modeling, leveraging alternative data, and scaling our data infrastructure.
Key Responsibilities
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.
Model Development & AI Governance
- 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.
Team Leadership & Development
- Drive best practices in model development, MLOps, and responsible AI.
- Promote cross-functional collaboration to maximize the value of data science across the organization.
Person Specification
Required
- 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.
Preferred
- Experience in fintech, digital lending, or embedded finance.
- Exposure to cloud platforms such as AWS, GCP, or Azure for data engineering and machine learning.
- Familiarity with graph analytics, network science, or behavioral data modeling.
- Knowledge of causal inference techniques and advanced experimentation methodologies.
- Prior experience in expanding data science functions into new markets.
- Master’s or PhD in Machine Learning, AI, Data Science, Statistics, Finance, or a related field.
We’re thrilled to have you join us as we reshape the financial landscape in emerging markets.
We believe in equal opportunities, we welcome applications from diverse backgrounds.