Data Analyst
Analyzes operational, product, and financial data to identify trends, build dashboards, and support cross-functional teams in optimizing fintech processes like fraud, risk, and rewards. Requires 3-7 years experience with SQL, Python, AI tools, and dashboarding.
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
- Track record of collaborating effectively with product, engineering, or operations teams
- 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
Bonus/Nice to have
- Experience building or deploying internal AI tools, automations, or agents to improve productivity or business operations
- Familiarity with financial systems, reconciliation workflows, or data integrity challenges
- Experience in fintech, credit/financial systems, fraud, risk, or customer lifecycle analytics
Compensation
- Annual starting salary range of $130,000-$200,000 + equity + benefits
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