Moniepoint - Data Analyst - Fraud
Requirements
• 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.
Responsibilities
• 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
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