Opportunity at
MoniepointSenior Data Scientist (Credit)
Moniepoint Inc. is a financial platform operating in Africa that provides payments, banking, credit, cross-border transactions, and business management tools. Recognized as Nigeria's largest merchant acquirer,…
Career Tools
About This Role
Moniepoint Inc. is a financial platform operating in Africa that provides payments, banking, credit, cross-border transactions, and business management tools. Recognized as Nigeria's largest merchant acquirer, the organization processes over $250 billion in digital payment transaction value annually and powers the majority of the nation's point-of-sale transactions. The company is seeking a Senior Data Scientist to oversee consumer lending decisions at scale. Working within the Consumer Credit team, this position…
Job Description
Moniepoint Inc. is a financial platform operating in Africa that provides payments, banking, credit, cross-border transactions, and business management tools. Recognized as Nigeria's largest merchant acquirer, the organization processes over $250 billion in digital payment transaction value annually and powers the majority of the nation's point-of-sale transactions.
The company is seeking a Senior Data Scientist to oversee consumer lending decisions at scale. Working within the Consumer Credit team, this position focuses on building the initial suite of credit risk models, designing experiments, and shaping strategies for customer acquisition, underwriting, and retention across Nigeria and Africa. The professional in this role will drive pricing, credit limit modeling, and model deployment while blending machine learning techniques with traditional methods to maintain healthy portfolio performance.
This opportunity suits a quantitative professional with extensive financial services experience who wants to influence real-time decisioning systems and mentor cross-functional product squads.
Responsibilities
- Develop and deploy credit scoring, affordability, and behavioral models to support underwriting, pricing, and collections
- Design and execute experiments to optimize approval rates, loss rates, and profitability
- Collaborate with product squads to integrate decision logic into real-time systems
- Maintain data quality, regulatory compliance, and ethical model use throughout decisioning processes
- Mentor product squads regarding experimentation and data-driven decision practices
- Provide models aimed at improving outcomes in user retention, churn management, and collections
Requirements
- More than 5 years of professional experience in data science, risk analytics, or decision science within the financial services sector
- Working knowledge of consumer lending, credit risk, and related regulatory considerations
- Proficiency in SQL and at least one programming or modeling language such as Python or R
- Direct experience with machine learning, A/B testing, churn management, and collections modeling
- Demonstrated capability to translate intricate analyses into clear recommendations for business stakeholders
- High ownership mindset suited for fast-paced, cross-functional team environments
Qualifications
- Degree or relevant qualifications in a quantitative field such as Statistics, Mathematics, Engineering, or a similar discipline
- Strong foundation in statistics
Core Skills
Benefits
- Attractive salary
- Pension
- Health insurance
- Monthly bonuses
- Access to a learning and development environment featuring knowledge sharing, training, and internal technical talks
- Additional benefits
Frequently Asked Questions
Answers are based only on the employer’s listing; where it doesn’t say, neither do we.
What is the remote status for the Senior Data Scientist (Credit) role?
The source posting specifies that the role is on-site, though a specific city location is not stated.
What experience is required for this position?
Candidates must have more than 5 years of experience in data science, decision science, or risk analytics within financial services, along with proficiency in SQL and Python or R.
What does the hiring process involve?
The hiring process consists of a preliminary recruiter phone call, a HackerRank coding exercise, a take-home assignment, a technical interview with a Data Science Team Lead, and a final behavioral and technical interview with the hiring manager.
Sample Interview Questions
AI-generated questions tailored to this specific role — a preview of the full practice set.
