Data Analyst

Responsibilities

• Analyze operational, product, and financial data to identify trends, diagnose issues, and surface actionable insights
• Build dashboards, reporting frameworks, and monitoring tools that improve visibility into system and business performance
• Partner with product managers, engineers, and risk/compliance teams to support the design of new features, workflows, and policies
• Evaluate and optimize business processes across the customer lifecycle (applications, onboarding, transactions, servicing, fraud, and rewards)
• Perform deep-dive investigations into anomalies, system issues, or partner escalations; help determine root causes and drive remediation
• Support forecasting, business reviews, and strategic planning with clear, data-driven analysis
• Contribute to improving data quality, documentation, and analytical rigor across the organization
• For senior candidates: provide guidance to teammates, lead medium-sized cross-functional projects, and influence strategic decisions

Requirements

• 3–7 years of experience in an analytical, operations, strategy, or data-focused role
• Strong proficiency with data analysis tools (SQL, Excel/Sheets, Python)
• Experience using AI tools in a professional setting (e.g., for workflows, analysis, automation, or insight generation)
• Demonstrated ability to integrate AI into day-to-day work (prompt design, model evaluation, data prep, or workflow optimization)
• Experience working with large datasets and building reliable reporting/dashboarding (Looker, Tableau, Omni, Mode, or similar)
• Solid understanding of business processes, KPIs, and analytical frameworks; able to independently break down ambiguous problems
• Excellent communication skills — able to translate complex analysis into clear insights for technical and non-technical partners
• Ability to manage multiple priorities, take ownership, and drive projects end-to-end
• Curiosity, attention to detail, and a passion for building well-structured analytical systems and business processes
• Nice to have: experience in fintech, credit/financial systems, fraud, risk, or customer lifecycle analytics