Worth AI is looking for a Senior Data Analyst to analyze and optimize data for credit decisioning, underwriting, and fraud prevention models, driving impactful decision-making through data insights in their fintech organization.
Requirements
- Advanced SQL skills and experience working with cloud data platforms (e.g., AWS Redshift, Athena, Snowflake, BigQuery).
- Strong experience with data visualization tools like Tableau, Power BI, or Looker, and the ability to build intuitive dashboards for business stakeholders.
- Solid understanding of credit risk concepts, underwriting processes, and key lending KPIs such as delinquency, charge-off rates, loss curves, and approval funnels.
- Exposure to AI/ML-based decision systems, especially in underwriting, fraud detection, or credit scoring contexts.
- Working knowledge of data engineering fundamentals and modern data stack tools (e.g., dbt, Airflow, ETL pipelines).
- Proficiency in Excel for detailed analysis and cross-functional reporting.
- Bonus: Experience with Python or other scripting languages for data analysis and automation.
Responsibilities
- Mine and analyze large-scale credit, transactional, and behavioral datasets to identify trends, anomalies, and insights that inform credit risk, underwriting, fraud, and pricing strategies.
- Write performant SQL queries to extract, transform, and analyze data across structured and semi-structured sources (including loan-level, customer, and bureau data).
- Design, build, and maintain interactive dashboards and reporting tools to support Finance, Risk, Credit, and Executive teams in monitoring key performance indicators.
- Partner with Data, Finance, Product and Engineering teams to define and track key metrics for credit performance, loss forecasting, and portfolio health.
- Support the development and ongoing evaluation of AI/ML models by providing exploratory data analysis, historical performance context, and business rule validation.
- Collaborate with data engineering and data science teams to ensure pipelines are reliable, secure, and meet both operational and regulatory standards.
- Automate recurring reports and analyses to improve visibility and reduce manual workflows across the credit and finance lifecycle.
Other
- 4+ years of experience in a data analytics or business intelligence role, ideally in a fintech, financial services, or credit risk environment.
- High standards for data integrity, governance, and regulatory compliance in a financial environment.
- Excellent communication and problem-solving skills, with the ability to present complex data insights to technical and non-technical stakeholders alike.
- Stay informed on regulatory and compliance requirements related to data usage in financial services (e.g., Fair Lending, ECOA, GLBA) and align analytics practices accordingly.
- Contribute to model governance efforts by ensuring documentation, auditability, and transparency of data inputs used in risk models and decision engines.
