Data Analyst - Fraud

• Skills: SQL, Git, Python
• Experiences: Mid-level
• Employments: Full-time
• Benefits: Health insurance, Paid time off, Pension matching, Performance bonuses

Description:

• Investigate fraud attacks, quantify their impact, and present findings to drive prioritization and response.
• Propose and refine rule-based mitigations in collaboration with fraud operations and engineering.
• Build and maintain reporting and dashboards to monitor fraud trends and key operational metrics.
• Collaborate with fraud operations, data scientists, engineers, and product managers to translate analytical insights into action.
• Proactively identify emerging patterns and flag risks before they escalate.

Requirements:

• Proven experience as a Data Analyst (Fraud) or similar role (4+ years).
• Strong problem-solving skills and advanced proficiency with SQL.
• Experience in fraud, risk, or financial services with an understanding of fraud attacks and mitigation trade-offs.
• Proactive mindset with some exposure to Python or scripting for data manipulation.
• Proficiency with a BI tool (e.g., PowerBI, Tableau) and spreadsheet tools (e.g., Excel).
• Strong stakeholder management and communication skills.
• Ability to work in fast-paced, cross-functional teams.
• Bachelor's degree in Computer Science, Statistics, Mathematics, Engineering, or related field.

Benefits:

• People-first culture prioritizing well-being and respect for all team members.
• Learning and development-focused environment with knowledge sharing and training opportunities.
• Attractive salary, pension, health insurance, annual bonus, and additional benefits.