Fintech Data Analyst - Credit Risk (Hybrid)

 DIRECTLY REPORTS TO:
Data Manager
 

MAIN AREA OF RESPONSIBILITY:
 

The Embedded Finance Data Analyst plays a critical role in supporting Sprout’s Fintech Operations, Product, and Business teams by transforming raw data into actionable insights that strengthen business growth, product discovery and development, operational efficiency, and risk management. This role enables strong decision-making across the organization.
 

KEY RESPONSIBILITIES:
 

Business Growth

• Analyze client usage patterns, portfolio performance, and adoption metrics to identify opportunities for growth across embedded finance products.
• Provide data-driven insights to support client segmentation, targeting, and prioritization for upsell, expansion, and product-led growth initiatives.
• Support Business and Growth teams with dashboards and reports that highlight client health, financial performance, revenue impact, and behavior trends.
• Evaluate the impact of campaigns, engagement initiatives, and employer-level performance to inform strategy and decision-making.

Product Discovery & Development

• Collaborate with UXR to interpret existing product and user data, helping identify user problems, market gaps, and opportunity areas.
• Support Product Managers in evaluating new product concepts through industry research, competitive benchmarking, and data-driven business projections.
• Collaborate with UXR to interpret existing product and user data, helping identify user problems, market gaps, and opportunity areas.
• Monitor and analyze key product metrics, including conversion funnels, adoption, penetration, and engagement, to uncover insights that inform feature improvements and user experience enhancements.
• Evaluate the performance of newly released features, PLG initiatives, and experiments by conducting structured post-launch impact analyses and recommending next steps.
• Present clear, data-backed insights that guide product direction, highlight risks or opportunities, and influence strategic decision-making across the product lifecycle.

Operations

• Monitor key operational metrics such as revenue, repayment behavior, aging transactions (e.g., 30+ /60+ /90+ DPD), borrower activity, and disbursement success rates.
• Support escalation handling by investigating transaction anomalies, reconciliation issues, SOA discrepancies, and deactivation-related concerns through data analysis.
• Maintain and execute recurring reports, including weekly balances, non-repayment monitoring, and due date compliance.
• Develop dashboards and automated monitoring tools to enhance visibility for Customer Advocates, Success Consultants, Fintech Operations, and partner banks.
• Identify manual or error-prone workflows and support Product and Engineering teams in designing and validating automation for operational scale.

QUALIFICATIONS & COMPETENCIES:
 

• 3–5+ years of experience in data analytics with required experience in fintech, ideally in lending, embedded finance, payments, or financial operations.
• Strong SQL skills and experience working with data platforms (e.g., Databricks)
• Experience building dashboards using Power BI, Databricks, and HubSpot. 
• Knowledge of developing data models for reports and analysis. Python skills is a plus.
• Working knowledge of financial products and embedded finance workflows, including money movement, risk controls, and repayment processes etc.
• Experience with Credit Risk. 
• Excellent problem-solving, investigative, and analytical thinking.
• Ability to translate complex data into simple, actionable insights for non-technical teams.
• Strong communication skills and high attention to detail.