(Remote) Data Analyst at Moniepoint

Moniepoint

Applications are invited from suitable and qualified candidates for the Position of (Remote) Data Analyst at Moniepoint.

About Moniepoint

Moniepoint, originally established as “TeamApt,” began by offering back-end services to Nigerian banks. In 2019, Moniepoint Inc. acquired a switching license in Nigeria, and in 2022, it was granted a banking license by the Central Bank of Nigeria, expanding its services to include business banking for Nigerian merchants. Moniepoint operates as a global business payments and banking platform, and it gained recognition as the first African investment by QED Investors. They specialize in creating infrastructure and distribution networks that make payment acceptance more accessible and provide payment solutions to empower businesses.

Summary

  • Company: Moniepoint
  • Job Title: Data Analyst – Fraud
  • Job Type: Full Time
  • Qualification: OND/BA/BSc/HND/MSc
  • Location: Remote
  • Deadline: Not Specified

Job Title: Data Analyst – Fraud

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What you’ll do

  • Investigate fraud attacks, quantify their impact, and present clear findings that drive prioritisation and response
  • Propose and refine rule-based mitigations, working with fraud operations and engineering to see them through to implementation
  • Build and maintain reporting and dashboards to monitor fraud trends, rule performance, and key operational metrics
  • Work closely with fraud operations, data scientists, engineers, and product managers to ensure analytical insights translate into action
  • Proactively identify emerging patterns and flag risks before they escalate

See Also:

Requirements for the Position of (Remote) Data Analyst at Moniepoint

To succeed in this role, you should have

  • Proven experience as a Data Analyst (Fraud),  or a similar role (4+ years, can be made up for with accomplishments)
  • Strong problem solving skills
  • Advanced proficiency with SQL. you’re comfortable writing complex queries to investigate and slice data across large datasets
  • Experience in fraud, risk, or financial services; you understand how fraud attacks work and how to think about mitigation trade-offs
  • A proactive mindset — you don’t wait to be asked; you spot something unusual and you dig in
  • Some exposure to Python or scripting for data manipulation and analysis
  • Proficiency with a BI tool (PowerBI, Looker, Tableau, Superset, Redash, or any other alternative)
  • Strong stakeholder management skills; you can communicate findings clearly to fraud operations, product managers, engineers, and senior leadership — and you know how to influence decisions with data across all of them.
  • Comfort working in fast-paced, cross-functional teams where priorities shift quickly.
  • Proficiency with a spreadsheet tool (Microsoft Excel or Google Sheets, or any other alternative)
  • Enjoy autonomy and a flat structure: we have millions of customers and a flat hierarchy so any individual can have an outsized impact
  • Excellent written and verbal communication skills
  • A drive to learn and master new technologies and techniques
  • A bachelor’s degree in Computer Science, Statistics, Mathematics, Engineering, or any other related field

Experience with the following would be a plus

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  • Data governance
  • Python or any other scripting language
  • Git or any other version control tool

What we can offer you

  • Culture – We put our people first and prioritise the well-being of every team member. We have built a company where all opinions carry weight and where all voices are heard. We value and respect each other and always look out for one another. Above all, we are human.
  • Learning – We have a learning and development-focused environment with an emphasis on knowledge sharing, training, and regular internal technical talks.
  • Compensation – You’ll receive an attractive salary, pension, health insurance, annual bonus, plus other benefits.

What to expect in the hiring process

  • A preliminary phone call with the recruiter.
  • Technical take-home task (SQL test).
  • Technical Interview with hiring manager.
  • A behavioural interview with the Head of Data Analytics/Science and Fraud Team.

Deadline

Not Specified

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