Data Analyst - Fraud

Remote; Remote, Nigeria·Posted today

python

Who we are Moniepoint is an all-in-one financial services platform for emerging markets and the second-fastest growing company in Africa.  Since 2019, Moniepoint’s technology has powered over 3 million people, offering personal and business banking, payment, credit and business management tools to help them succeed. Moniepoint processed $182 billion in 2023 and currently processes the majority of the POS transactions in Nigeria. Curious about what makes Moniepoint an incredible place to work? <a href="https://moniepoint.com/blog">Check out posts on how we cultivate a culture of innovation, teamwork, and growth.</a> What you will get to do <ul> <li>Investigate fraud attacks, quantify their impact, and present clear findings that drive prioritisation and response</li> <li>Propose and refine rule-based mitigations, working with fraud operations and engineering to see them through to implementation</li> <li>Build and maintain reporting and dashboards to monitor fraud trends, rule performance, and key operational metrics</li> <li>Work closely with fraud operations, data scientists, engineers, and product managers to ensure analytical insights translate into action</li> <li>Proactively identify emerging patterns and flag risks before they escalate</li> </ul> To succeed in this role, you should have <ul> <li>Proven experience as a Data Analyst (Fraud),  or a similar role (4+ years, can be made up for with accomplishments)</li> <li>Strong problem solving skills</li> <li>Advanced proficiency with SQL. you're comfortable writing complex queries to investigate and slice data across large datasets</li> <li>Experience in fraud, risk, or financial services; you understand how fraud attacks work and how to think about mitigation trade-offs</li> <li>A proactive mindset — you don't wait to be asked; you spot something unusual and you dig in</li> <li>Some exposure to Python or scripting for data manipulation and analysis</li> <li>Proficiency with a BI tool (PowerBI, Looker, Tableau, Superset, Redash, or any other alternative)</li> <li>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.</li> <li>Comfort working in fast-paced, cross-functional teams where priorities shift quickly.</li> <li>Proficiency with a spreadsheet tool (Microsoft Excel or Google Sheets, or any other alternative)</li> <li>Enjoy autonomy and a flat structure: we have millions of customers and a flat hierarchy so any individual can have an outsized impact</li> <li>Excellent written and verbal communication skills</li> <li>A drive to learn and master new technologies and techniques</li> <li>A bachelor’s degree in Computer Science, Statistics, Mathematics, Engineering, or any other related field</li> </ul> Experience with the following would be a plus <ul> <li>Data governance</li> <li>Python or any other scripting language</li> <li>Git or any other version control tool</li> </ul> What we can offer you <ul> <li>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.</li> <li>Learning - We have a learning and development-focused environment with an emphasis on knowledge sharing, training, and regular internal technical talks.</li> <li>Compensation - You’ll receive an attractive salary, pension, health insurance, annual bonus, plus other benefits.</li> </ul> What to expect in the hiring process <ul> <li>A preliminary phone call with the recruiter.</li> <li>Technical take-home task (SQL test).</li> <li>Technical Interview with hiring manager.</li> <li>A behavioural interview with the Head of Data Analytics/Science and Fraud Team.</li> </ul> Moniepoint is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees and candidates.

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