Data Scientist

Inizio Partners Corp•San Diego, CA

13d•Hybrid

About The Position

As the Staff Data Scientist – Credit Strategy , you will design, deploy, and optimize end-to-end credit strategies that balance growth, profitability, and credit risk for a small-business lending portfolio. You will develop policy frameworks for approvals, segmentation, limits, and pricing; embed forward-looking risk signals; and build monitoring to keep portfolio performance within loss tolerances. You will partner with client and internal leaders across Risk, Product, Engineering, and Underwriting to operationalize decisioning, enable rapid experimentation, and create resilient portfolios that are attractive to debt investors on a risk-adjusted basis.

Requirements

7+ years of hands-on experience designing, calibrating, and managing credit strategies for cash advance / short-duration small business credit products; prior MCA credit strategy experience
Strong experience overseeing model deployment, execution, and monitoring within a production environment; ML Ops experience is highly preferred
Masters degree in Data Science, Statistics, Economics, Finance, or a related quantitative discipline
Strong SQL and Python proficiency; ability to work with large datasets and build reproducible analytical workflows.
Excellent communication, presentation, and story-building skills in a consulting/client-facing setup.
Demonstrated ability to lead cross-functional initiatives end-to-end and coordinate with offshore delivery teams.
Bachelors degree in a related quantitative field such as Data Science, Statistics, Mathematics, Economics, Finance, or Engineering required.

Nice To Haves

Masters degree in Data Science, Statistics, Economics, Finance, or a related quantitative discipline is a plus

Responsibilities

Design and deploy innovative approval, qualification, and segmentation strategies that maximize application approval rates while achieving credit loss targets
Develop and maintain underwriting policies that define minimum acceptance criteria and policy declines for segments outside clients risk appetite
Create statistically grounded credit limit assignment frameworks that optimize lifetime customer value while managing downside risk
Design pricing and interest rate strategies, including testing frameworks, to ensure adequate loss coverage, strong borrower selection, and high customer take-up rates
Optimize data collection strategies by balancing the information value of data against customer friction and operational cost
Partner closely with the manual underwriting team to build a hybrid risk framework that integrates analytical strategies with expert manual review, ensuring consistent execution and continuous feedback loops. This would require innovative credit strategy tooling to create differentiated credit pathways for applications based on their profile, loan amount exposure and complexity of underwriting required
Collaborate with Product, Engineering, and Data Science teams to design and deploy scalable infrastructure that enables rapid iteration and refinement of credit strategies
Establish robust portfolio monitoring and reporting processes to track approval rates, credit performance, and risk metrics against expectations
Apply a thoughtful, forward-looking approach to portfolio construction to ensure assets are resilient across economic cycles and attractive to debt investors on a risk-adjusted basis
Incorporate macroeconomic trends and forward-looking risk signals into credit strategy to ensure ongoing relevance in evolving market conditions