Senior Data Scientist (Credit Risk)

Key Responsibilities

• Building, maintaining and enhancing credit risk models for lending portfolios.
• Extract, clean and manipulate large data sets using SQL and Python; build pipelines and analytics to perform model and portfolio monitoring.
• Perform exploratory data analysis (EDA) to identify portfolio trends, drivers of loss performance (vintage, credit bands, borrower attributes, macro factors) and provide insight into model deviations.
• Maintain forecast deliverables: monthly/quarterly loss forecasts by vintage and segment, stress and scenario analyses, sensitivity testing.
• Provide commentary and insights to business stakeholders on credit policy assumptions, model health, and emerging portfolio risks.
• Automate reporting, dashboards and pipelines to streamline model monitoring and improve efficiency and accuracy.
• Document model methodologies, assumptions, data sources and results in clear, audit-ready format consistent with risk governance requirements.
• Participate in governance and review of credit model methodology, model validation support and liaise with external auditors or regulators where needed.
• Continuously identify opportunities to improve credit decisioning accuracy, data infrastructure, modeling techniques, and integrate advanced statistical or machine-learning techniques as appropriate.

Qualifications

• Minimum of 8 years’ hands-on experience in credit risk modeling and portfolio monitoring.
• Strong programming skills in Python/SQL for data analysis, modeling and automation.
• Solid background in Probability & Statistics.
• Experience with pricing and price optimization along with analytics and monitoring related to pricing.
• Experience with credit risk modeling methodologies: Scorecard models, XGBoost, time-series analysis, vintage modeling, roll-rate curves, survival analysis or logistic regression in consumer credit risk context.
• Familiarity with data visualization tools (e.g., Tableau, Python Widgets) or dashboarding.
• Excellent analytical and critical thinking skills; ability to interpret results, identify trends, draw actionable insights and communicate clearly to non-technical stakeholders.
• Strong documentation skills and experience in preparing audit-ready deliverables (methodologies, assumptions, model validation support).
• Master’s degree in Economics, Statistics, Mathematics, Data Science or a related quantitative discipline (PhD preferred, but not required).

Preferred

• Experience in lending (personal loans or credit cards) or fintech lending environment.
• Experience with credit risk modeling (development & monitoring).
• Experience working with credit decisioning engines such as Oscilar, TakTile etc….
• Experience working in CKLightbox environment.
• Experience working in the GCP environment.
• A Passion for fintech, agile environment, ability to work both independently and in a collaborative, fast-paced team.

Additional Information

All your information will be kept confidential according to EEO guidelines.

Achieve well-being with:

• 401(k) with employer match
• Medical, dental, and vision with HSA and FSA options
• Competitive vacation and sick time off, as well as dedicated volunteer days
• Access to wellness support through Employee Assistance Program, physical and mental health wellness programs
• Pet care discounts for your furry family members
• Financial support in times of hardship with our Achieve Care Fund
• A safe place to connect and a commitment to diversity and inclusion through our six employee resource groups

Note: We will be unable to facilitate H1-B Visa transfer or sponsorship, along with STEM-OPT Visa.

Note: This role will be working hybrid out of our San Mateo, CA office.

Salary Range: $165,000 to $185,000 salary + bonus + benefits.