Senior Data Analyst - Fraud

London, United Kingdomvia Moniepoint CareersPosted Aug 3, 2026
Match with my CV

Technical skills

PythonSQLData analysisBusiness intelligenceData science

Methods

L&D

Role signals

Recruiting

About this role

Who We Are

Moniepoint Inc. is Africa’s all-in-one financial platform, helping 20 million businesses and individuals access seamless payments, banking, credit, cross-border, and business management tools each month.

As Nigeria’s largest merchant acquirer, we power most of the country’s point-of-sale (POS) transactions. Through our subsidiaries, Moniepoint Inc. processes over $250 billion in digital payment transaction value annually.

Curious about what makes Moniepoint an incredible place to work? Check out posts on how we cultivate a culture of innovation, teamwork, and growth.

What you will get to 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

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
  • 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.
  • Moniepoint is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees and candidates.

Before you apply

  • 1Which parts of your CV prove experience with Python, SQL, and Data analysis?
  • 2Which recent work examples would make your application stronger for this role?
  • 3What details from the original source listing should you confirm before applying?

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