Data Analyst - Fraud

Moniepoint, BRM; Greater London; On-site; GBP 55,000 - 75,000; Full time

Benefits offered by this job

Health insurance

Annual bonus

Pension

Job summary

Moniepoint is seeking a Data Analyst (Fraud) to investigate fraud attacks, quantify impact, and present findings to drive response. You will build and refine rule-based mitigations with fraud operations and engineering, and develop dashboards tracking fraud trends and rule performance.

Collaboration with data scientists, engineers, and product managers is essential to translate insights into action. The role requires 4+ years in data analysis (fraud or similar), strong problem solving, SQL

Qualifications

Responsibilities

Job description

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.

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 raise

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.