Data Science Lead

We are seeking a high-energy Lead Data Scientist with 5+ years of experience in predictive modeling to drive measurable bottom-line impact. Reporting to the Data Analytics Lead, you will own credit risk analytics (Paystack MFB), business forecasting, and strategic predictive projects. You will collaborate with the broader data team and business heads to deploy high-quality, meticulously crafted analytical products that solve complex business challenges.

We’ll trust you to own

Advanced Analytics & Model Ownership

• Strategy & Roadmap: Define the advanced analytics vision by leveraging business acumen and stakeholder relationships to prioritize high-impact projects.
• Infrastructure: Identify and source the tooling and frameworks required to scale advanced analytical capabilities.
• Risk & Forecasting: Develop and maintain core credit risk models (PD/LGD/EAD, default, segmentation) and business forecasting frameworks (revenue, volume, margins) under varying scenarios.
• Optimization: Ensure model integrity through continuous monitoring, back-testing, stress-testing and documentation for auditors and regulators.

Data Lifecycle & Collaboration

• Extract and refine datasets for modeling, partnering with Data Engineering to automate pipelines and ensure rigorous data governance.

You’ll thrive in this role if you

• Passion: Have a deep interest and curiosity in advanced analytics.
• Collaborative: Have exceptional stakeholder management abilities.
• Resilient: Do whatever it takes to make your team successful, no matter the issue—whether sourcing data or getting strategic buy in.
• Communication: Are an excellent and empathetic communicator both verbally and in writing.

Required Skills & Experience:

• Master’s in a quantitative field (Statistics, Economics, Data Science, or similar).
• 5+ years in predictive modeling or data science, ideally within fintech or lending.
• Expert in statistical modeling and time-series forecasting with a proven track record of implementation.
• Advanced SQL for ETL/analysis and expert Python (Pandas, NumPy, Scikit-learn, Statsmodels).
• Experience in building credit risk models (PD, LGD, EAD)
• Experience building and maintaining robust model pipelines.
• Proven ability to translate complex quantitative results into clear, actionable insights for non-technical stakeholders.

Bonus points if you have

• Experience in building application and behaviour scorecards in the credit risk space and in influencing lending decisions
• Experience with dbt, Airflow for orchestration and GitHub for change control
• Experience in using AI to improve quality and efficiency of workflows