Data Analyst - Fraud

Job description

• 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

Requirements

Education: Bachelor's degree Experience: 5 years Languages: English