Senior Data Scientist (Credit)

Description

The company is an all-in-one financial platform in Africa, serving about 20 million businesses and individuals each month with payments, banking, credit, cross-border and business management tools.

In Nigeria, the company is the largest merchant acquirer and handles most point-of-sale (POS) transactions. Its subsidiaries process more than $250 billion in digital payment value each year.

Data drives decisions across the company, which puts customers first. This role supports consumer lending at scale by building the models, experiments and insights used to acquire, underwrite and retain millions of customers across Nigeria and Africa.

You will work with the Consumer Credit team on pricing, credit limit modelling and how credit models get deployed. You will help shape risk ranking, product offers and data infrastructure so customers receive well-matched personalised offers.

You will build the first set of credit risk models and help the team decide when machine learning fits better than traditional methods. The role sits where data science, credit risk and product meet, turning complex data into decisions that grow the business while keeping the loan portfolio healthy.

The hiring process starts with a call with a recruiter, then a coding test on HackerRank covering core data science theory (math, statistics, linear algebra) and Python basics (data structures and algorithms). Next comes a take-home assignment, reviewed in depth in a technical interview with a Lead from the Data Science Team, followed by a behavioural and technical interview with the hiring manager.

Responsibilities

• Build and deploy credit scoring, affordability and behavioural models that support underwriting, pricing and collections
• Design and run experiments that improve approval rates, loss rates and profitability
• Work with product squads to put decision logic into real-time systems
• Make sure data quality, compliance and ethical model use hold across all decisioning
• Coach product squads on experimentation and data-driven decision-making
• Build models that improve collections, churn management and user retention

Requirements

• Strong grounding in statistics, with a degree or qualification in a quantitative field such as statistics, mathematics or engineering
• 5+ years of experience in data science, decision science or risk analytics within financial services
• Working knowledge of credit risk, consumer lending and the regulations that apply to them
• Proficiency in SQL and at least one modelling or programming language, such as Python or R
• Experience with A/B testing, machine learning, collections modelling and churn management
• Ability to turn complex analysis into clear recommendations for business stakeholders
• A strong sense of ownership and comfort working in fast-moving, cross-functional teams

Conditions

The company is an equal opportunity employer that values diversity and works to keep its environment inclusive for employees and candidates.

Benefits

• A competitive salary, pension, health insurance, monthly bonuses and other benefits
• A learning-focused environment with knowledge sharing, training and regular internal technical talks
• A culture that puts people's well-being first, where every opinion counts and colleagues look out for one another