Opportunity at
MoniepointSenior Data Scientist (Credit)
Moniepoint Inc. is a financial platform operating in Africa that provides millions of individuals and businesses with access to digital payments, banking, credit, and tools for…
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About This Role
Moniepoint Inc. is a financial platform operating in Africa that provides millions of individuals and businesses with access to digital payments, banking, credit, and tools for business management. As a major merchant acquirer handling high volumes of point-of-sale transactions and digital payment values annually, the organization relies heavily on data to guide its business strategies. The company is currently searching for a Senior Data Scientist (Credit) to join its Consumer…
Job Description
Moniepoint Inc. is a financial platform operating in Africa that provides millions of individuals and businesses with access to digital payments, banking, credit, and tools for business management. As a major merchant acquirer handling high volumes of point-of-sale transactions and digital payment values annually, the organization relies heavily on data to guide its business strategies.
The company is currently searching for a Senior Data Scientist (Credit) to join its Consumer Credit team on a full-time, on-site basis. In this position, the professional will shape consumer lending operations by creating predictive models, conducting experiments, and generating insights to support customer acquisition, underwriting, and retention strategies across multiple African markets.
This role suits an analytical specialist with a strong background in financial services who can bridge the gap between data science, credit risk, and product management. The successful candidate will design the initial suite of credit risk models, establish pricing frameworks, optimize credit limits, and deploy machine learning solutions alongside traditional methodologies. Responsibilities span across developing behavioral and affordability models, running optimization experiments, and guiding product squads on best practices for data-driven decisions and experimentation.
Responsibilities
- Build and implement behavioral, affordability, and credit scoring models for underwriting, pricing, and collections.
- Plan and execute experiments aimed at balancing approval rates, profitability, and loss rates.
- Collaborate with product teams to integrate decision logic into real-time systems.
- Monitor data quality, ethical model usage, and regulatory compliance across decision workflows.
- Guide product squads on experimentation methodologies and data-driven choices.
- Deliver models designed to improve user retention, churn management, and collections outcomes.
Requirements
- More than five years of professional experience in risk analytics, decision science, or data science within the financial services sector.
- Working knowledge regarding consumer lending, regulatory requirements, and credit risk.
- Strong proficiency in SQL and at least one programming or modeling language such as Python or R.
- Practical background in machine learning, A/B testing, churn management, and collections modeling.
- Capability to convert intricate data analyses into straightforward recommendations for business stakeholders.
Qualifications
- A degree or relevant qualification in a quantitative academic discipline like Statistics, Mathematics, Engineering, or a related field.
Core Skills
Benefits
- Attractive salary package
- Pension plan
- Health insurance coverage
- Monthly bonuses
- Additional employee benefits and learning development opportunities
Frequently Asked Questions
Answers are based only on the employer’s listing; where it doesn’t say, neither do we.
What is the employment type for this role?
This is a full-time position.
Is this a remote position?
No, the job posting specifies an on-site working arrangement.
What salary is offered for the Senior Data Scientist position?
The specific salary amount is not stated in the job posting, though the role includes an attractive salary along with bonuses, pension, and health insurance.
What experience is required to apply?
Candidates must have over five years of experience in data science, decision science, or risk analytics within financial services, alongside proficiency in SQL and Python or R.
Sample Interview Questions
AI-generated questions tailored to this specific role — a preview of the full practice set.
