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Data Scientist - Credit Risk
9.0/10
Divine
$135,000 – $237,000 USD
Remote
mid
about 2 months ago
analyticscryptofintechPythonSQLGrafanaPrometheusMetabaseBlockchain dataDuneShovel
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Description
What you'll do
- •Monitor credit risk models, including underwriting, loss forecasting, and fraud detection, and iterate based on observed portfolio performance.
- •Design, build, and maintain scalable data pipelines, monitoring infrastructure, and dashboards to track portfolio health, user behavior, and key risk indicators.
- •Partner with product, research, and engineering teams to define north star metrics and translate them into measurable, actionable credit and growth strategies.
- •Design and analyze A/B tests, quasi-experiments, and causal inference studies to evaluate the impact of product and policy changes.
- •Produce portfolio monitoring and investigative analyses, making recommendations based on findings.
- •Translate complex quantitative findings into clear, compelling narratives for product, leadership, and cross-functional stakeholders.
Requirements
- •4+ years of experience in decision science, credit risk analytics, or a closely related quantitative role within fintech or consumer lending.
- •Deep proficiency in Python and SQL; comfortable owning analyses end-to-end from raw data to recommendation.
- •Strong understanding of credit risk modeling concepts, including PD/LGD modeling, scorecard development, reject inference, vintage analysis, and risk segmentation.
- •Demonstrated experience monitoring credit risk metrics and portfolio performance, including loss forecasting and underwriting model improvement.
- •Proven ability to influence and collaborate with cross-functional teams and senior stakeholders, with a track record of translating analytical findings into accessible, actionable insights.
- •Experience designing and evaluating experiments (A/B tests, holdout groups, or causal inference frameworks) in a consumer product context.
- •Comfortable with ambiguity and biased toward action; thrives with minimal oversight and brings strong problem-solving skills and sharp attention to detail.
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