Senior Credit Strategy Data Analyst

About the Role

We are expanding our earned wage access (EWA) offering and seeking a Credit Strategy Data Analyst with strong analytical skills and experience working with consumer credit, open-banking data, or real-time underwriting strategies.

This role focuses on the design and analysis of models, data foundations, reporting, and data-driven strategies to improve credit risk management for the EWA product. You’ll be instrumental in shaping strategies that balance growth and portfolio credit risk.

What You’ll DoStrategy Support

• Support design and monitoring of EWA underwriting strategies and forecasting tools.
• Translate analytical findings into clear recommendations for credit policies.
• Support champion/challenger tests and experiment design for EWA risk strategies.
• Assist in designing exposure limits, eligibility rules, and verification checks.

Credit Analytics & Data Science

• Query, clean, and analyze large bank transaction datasets using SQL and Python, or R/SAS).
• Build dashboards, reports and durable data assets to track customer behavior and credit performance.
• Perform EDA, feature engineering, and data quality checks to drive trusted insights.
• Prepare model inputs, evaluate new data sources (including open-banking data), and track model performance.
• Analyze performance of underwriting strategies and identify opportunities to improve accuracy and reduce losses.
• Learn and introduce new analytical tools and techniques relevant to credit risk.

Collaboration & Communication

• Partner with Product, Engineering, Data Science, and Operations to implement updates to policies and decisioning logic.
• Support the coordination of initiatives with data suppliers.
• Package insights into crisp narratives and presentations for stakeholders.

What You’ll BringExperience

• Degree in Engineering, Computer Science, Statistics, Economics, Finance, or related; or equivalent experience. Advanced degree is a plus.
• 5+ years of analytics/data science experience.
• 2+ years of experience in consumer lending, fintech, or banking credit risk (subprime experience is a plus).
• Exposure to earned wage access, overdraft-alternatives, or cash-flow-based lending products is a strong plus.
• Experience working with bank transaction data and other very large financial datasets.

Technical Skills

• Proficiency in SQL and at least one analytical language (Python preferred; R or SAS acceptable).
• Experience with visualization tools such as Tableau (preferred), Power BI, Looker; strong skills with Excel/Google spreadsheets.
• Exposure to experimentation design and tracking.
• Experience cleaning, joining, and analyzing large datasets in a cloud data warehouse environment (i.e. Snowflake, BigQuery, Redshift).
• Familiarity with open-banking data supplier integrations is desirable (i.e. Plaid, MX, Finicity).

Attributes

• Strong analytical mindset and attention to data quality.
• Ability to translate data findings into clear recommendations.
• Curiosity, ownership mindset, and comfort working in a fast-moving environment.
• Collaborative approach and willingness to learn new data tools and risk frameworks.

Base salary is $101,000-150,000 annually. Individual pay is based on factors unique to each candidate, including skill set, experience, and other job-related reasons.