About the role
We are an early-stage SME lending business where data drives every decision: who we lend to, how we price risk, and how we grow. You'll turn application, transaction, and repayment data into insights that shape credit, growth, and product. This is a hands-on, high-ownership role working directly with founders, credit, and product, with room to help build the analytics function from the ground up.
Responsibilities:
- Own dashboards and reporting on portfolio health, disbursements, collections, and unit economics.
- Write and optimize SQL against our loan, application, and payments data.
- Analyze borrower behavior, delinquency, and repayment trends to inform credit policy.
- Run funnel and acquisition analysis with the growth team using Google Analytics.
- Support underwriting with cohort analysis and simple predictive models (e. g., default / propensity scoring).
Requirements:
- 2-3 years in a data analyst role, ideally in fintech, lending, or financial services.
- Strong SQL and hands-on Tableau (or similar BI tool).
- Working knowledge of Google Analytics.
- Exposure to machine learning; you've built or worked with predictive models (Python or R).
- Clear communicator who thrives in an ambiguous, fast-moving environment.
Good to have skills:
- Consumer or SME credit risk / underwriting / collections analytics.
- Python (pandas, scikit-learn) and cloud data warehouses (BigQuery, Snowflake, Redshift).