Sr. Data Scientist (Credit Risk)

TL;DR

Sr. Data Scientist (Credit Risk) (Python/SQL): Building and enhancing credit risk models for lending portfolios with an accent on loss forecasting, model/portfolio monitoring pipelines, and audit-ready governance documentation. Focus on translating large-scale analytics into actionable insights for business stakeholders and automating dashboards and reporting to improve model health and decisioning accuracy.

Location: Hybrid in the Phoenix, AZ and San Francisco, CA metro market; 100% remote in other approved locations (United States)

Salary: $165,000–$185,000 + bonus + benefits

Company

hirify.global is a digital personal finance company using proprietary data and analytics to deliver personalized financial solutions.

What you will do

• Build, maintain, and enhance credit risk models/policies to monitor lending portfolios.
• Extract, clean, and manipulate large datasets using SQL and Python; build pipelines and analytics for model and portfolio monitoring.
• Run exploratory data analysis (EDA) to identify portfolio trends, loss drivers, and model deviations.
• Maintain monthly/quarterly loss forecasts by vintage and segment, including stress/scenario analyses and sensitivity testing.
• Automate reporting, dashboards, and pipelines to streamline model monitoring and improve efficiency and accuracy.
• Document methodologies and assumptions in clear, audit-ready formats and support governance/model validation and external audits/regulators.

Requirements

• Minimum 8 years of hands-on experience in credit risk modeling and portfolio monitoring (e.g., charge-offs, delinquencies, vintage analysis, roll-rates).
• Strong programming skills in Python and SQL for data analysis, modeling, and automation.
• Solid background in probability and statistics.
• Experience with pricing and price optimization analytics and monitoring.
• Experience with credit risk modeling methodologies such as scorecards, XGBoost, time-series analysis, vintage modeling, roll-rate curves, survival analysis, or logistic regression (consumer credit context).
• Excellent documentation skills for audit-ready deliverables and model validation support.

Nice to have

• Experience in lending (personal loans or credit cards) or fintech lending environments.
• Experience with credit decisioning engines (e.g., Oscilar, TakTile) and/or CKLightbox.
• Experience working in GCP.
• Experience with credit decisioning engines and/or advanced statistical/ML techniques in a fintech/agile environment.

Culture & Benefits

• Hybrid and remote work opportunities.
• 401(k) with employer match; medical, dental, and vision with HSA and FSA options.
• Competitive vacation and sick time off plus dedicated volunteer days.
• Wellness support via Employee Assistance Program, Talkspace, and fitness discounts.
• Up to $5,250 paid back for eligible education expenses; hirify.global Care Fund for hardship support.
• Diversity and inclusion supported through six employee resource groups.

Hiring process

• Interviews to assess credit risk modeling experience, Python/SQL skills, and ability to communicate insights to non-technical stakeholders.
• Evaluation of documentation/governance readiness and experience supporting model validation and audits.