Data Analyst - Fraud

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

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

Data governance

Python or any other scripting language

Git or any other version control tool

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.

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.