Opportunity at
MoniepointSenior Data Analyst - Fraud
Moniepoint seeks a Senior Data Analyst - Fraud to join their team in a full-time, on-site capacity. As an all-in-one financial platform in Africa, Moniepoint serves…
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About This Role
Moniepoint seeks a Senior Data Analyst - Fraud to join their team in a full-time, on-site capacity. As an all-in-one financial platform in Africa, Moniepoint serves millions of individuals and businesses, processes massive annual digital payment values, and operates as Nigeria's largest merchant acquirer for point-of-sale transactions. In this position, the professional will examine fraudulent incidents, measure their effects, and deliver insights to guide response strategies and priorities. The ideal…
Job Description
Moniepoint seeks a Senior Data Analyst - Fraud to join their team in a full-time, on-site capacity. As an all-in-one financial platform in Africa, Moniepoint serves millions of individuals and businesses, processes massive annual digital payment values, and operates as Nigeria's largest merchant acquirer for point-of-sale transactions. In this position, the professional will examine fraudulent incidents, measure their effects, and deliver insights to guide response strategies and priorities. The ideal candidate enjoys autonomy within a flat organizational structure and thrives in a rapid, cross-functional setting where goals can change swiftly.
The role involves collaborating alongside engineering, product management, data science, and fraud operations groups to turn analytical findings into concrete actions. Team members build and update dashboards to track operational metrics, fraud patterns, and defense rule effectiveness. Furthermore, the analyst will design and refine rule-based mitigations while proactively spotting emerging risks. This position suits an analytical professional who combines technical skills with strong stakeholder management abilities to influence decision-making across leadership and operational teams.
Responsibilities
- Investigate fraudulent attacks, measure their financial and operational impact, and present actionable findings.
- Develop and refine rule-based defenses in collaboration with engineering and fraud operations teams.
- Construct and manage dashboards and reports to track key operational metrics and fraud trends.
- Partner with product managers, data scientists, engineers, and fraud operations to turn insights into solutions.
- Proactively detect emerging patterns and identify risks before they grow.
Requirements
- At least four years of relevant experience as a Fraud Data Analyst or in a comparable role.
- Advanced proficiency in writing complex SQL queries to examine large datasets.
- Practical background in financial services, risk, or fraud mitigation.
- Familiarity with spreadsheet applications such as Google Sheets or Microsoft Excel.
- Some exposure to Python or data scripting languages.
- Experience using Business Intelligence platforms such as Tableau, Looker, PowerBI, Redash, or Superset.
- Strong communication and stakeholder management abilities across technical and leadership tiers.
Qualifications
- A bachelor degree in Mathematics, Statistics, Computer Science, Engineering, or a related discipline.
- Prior background working with data governance frameworks.
- Familiarity with version control tools like Git.
Core Skills
Benefits
- Competitive financial compensation package.
- Pension contributions.
- Health insurance coverage.
- Annual bonus.
- Access to a learning and development environment featuring knowledge sharing and internal technical talks.
Frequently Asked Questions
Answers are based only on the employer’s listing; where it doesn’t say, neither do we.
What is the location and remote status for this role?
The job posting states the role is on-site, but does not specify a geographic location.
What type of employment is this?
This is a full-time position.
What is the salary for this position?
The salary is not specified in the job posting.
What does the hiring process involve?
The recruitment steps include an initial recruiter phone call, a technical take-home SQL test, a technical interview with the hiring manager, and a behavioral interview with the Head of Data Analytics/Science and the Fraud Team.
Sample Interview Questions
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