Senior Data Scientist

We invite applications from suitably qualified candidates.

• We are looking for a Senior Data Scientist to join our team and lead the development of advanced credit risk models, strategic insights, and business intelligence tools that drive high repayment rates, operational efficiency, and portfolio growth. This role is critical in strengthening our risk management framework and scaling our impact across the continent.

Core Responsibilities Credit Risk Model Development

• Develop, test, and iterate credit risk models on a quarterly basis.

• Ensure repayment rates consistently exceed 95%, with a default rate of less than 3% across all portfolios.

Strategic Data Insights

• Provide data-driven insights and reports to portfolio leads, senior management, and external stakeholders.

• Translate findings into actionable strategies to enhance performance and mitigate risks.

Data Extraction, Cleaning & Mining

• Lead the end-to-end processes of data extraction, cleaning, transformation, and mining.

• Build datasets that power descriptive, predictive, and spatial models to support decision-making.

Cross-Functional Experimentation

• Design and lead experiments across business units to optimize products, processes, and risk strategies.

• Measure and communicate results to ensure learnings drive continuous improvements.

Business Intelligence Development

• Develop and enhance BI tools to maximize product efficiency, improve Lifetime Value (LTV), and gross margins.

• Deliver at least two major BI tool enhancements or new feature implementations per quarter.

Real-Time Dashboards & Reporting

• Build and maintain real-time dashboards with a 99% uptime and accuracy target.

• Deliver monthly finance reports on-time and with > 99% accuracy in reports. Continuously add to exception reports to enhance portfolio quality and leverage AI + automation to improve reporting processes. 

• Ensure accurate and timely lender reporting, portfolio impact analysis, and internal business reporting.

Documentation & Transparency

• Maintain clear documentation of models, experiments, and workflows to ensure reproducibility and transparency.

Mentorship & Team Leadership

• Mentor junior data scientists and analysts, fostering a collaborative, learning-driven culture.

• Lead the data science team in setting priorities, managing workloads, and delivering high-quality outputs.

Task Delegation & Ad Hoc Priorities

• Execute tasks assigned by the CEO, COO, Data Science Manager or CDO, prioritizing based on organizational goals and impact.

Key Performance Indicators (KPIs)

• LMS Accuracy: Achieve and maintain ≥ 98% accuracy in Learning Manage...