Senior Credit Risk Analyst

COMPANY OVERVIEW:

The company a global leader in enterprise-grade data analytics and AI solutions, committed to empowering businesses across various industries with cutting-edge technology and expert insights. Backed by a top private equity firm, they drive innovation through significant investments and an entrepreneurial spirit.

They focus on delivering advanced Data Analytics & AI Solutions. By combining sophisticated technology with subject matter expertise, they deliver material impact on clients' topline and streamline their operations. They specialize in providing tailored solutions across financial services, CPG, legal, pharma, life sciences, retail and logistics, helping them build robust data analytics and AI capabilities.

With a client base spanning 30 countries, they have a global presence to enables them to offer localized expertise with a worldwide perspective.

POSITION OVERVIEW:

We are seeking a Senior Credit Risk Analyst with strong unsecured lending experience to support client's consumer credit products. This role will focus on credit card and personal loan portfolios, leveraging data to drive risk strategies, optimize underwriting, and improve portfolio performance.


You will work closely with cross-functional partners in Risk, Product, Data Science, and Engineering to design, implement, and monitor credit risk strategies that balance growth, risk, and customer experience.


RESPONSIBILITIES:

• Develop, implement, and monitor credit risk strategies for unsecured lending products (with a strong focus on credit cards).
• Analyze portfolio performance, customer behavior, and risk trends to identify opportunities to improve approval rates, loss performance, and profitability.
• Design and execute A/B tests and experiments to evaluate new risk policies, cutoffs, and treatment strategies.
• Build and maintain dashboards, reports, and performance tracking for key risk metrics (e.g., delinquency, losses, vintage curves, line utilization, approval/decline rates).
• Partner with data science and modeling teams to translate model outputs into actionable strategies and policy rules.
• Use SQL and Python to extract, clean, and analyze large datasets from multiple sources.
• Present insights, recommendations, and business cases to senior stakeholders in a clear, structured manner.
• Support regulatory and compliance requirements by ensuring risk strategies and analyses meet internal and external standards.
• Contribute to continuous improvement of data, tools, and processes within the Credit Risk and Analytics function.

PREFERRED PROFILE:

• Bachelor's degree in a quantitative field (e.g., Statistics, Mathematics, Economics, Engineering, Computer Science, Finance) or equivalent practical experience.
• 5+ years of hands-on experience in Credit Risk within unsecured lending: ideally in: Credit cards (strongly preferred), and/or Personal loans or other unsecured consumer lending products.
• Strong SQL skills with demonstrated experience querying and manipulating large, complex datasets.
• Proficiency in Python for data analysis, modeling support, and automation (e.g., pandas, NumPy, basic visualization libraries).
• Proven track record of using analytics to solve business problems in credit risk (e.g., underwriting, line management, pricing, collections, fraud/risk trade-offs).
• Solid understanding of core credit risk concepts: scorecards, cutoffs, PD/LGD/EAD, vintage analysis, loss curves, risk-based pricing, and portfolio segmentation.
• Strong problem-solving skills with the ability to structure ambiguous problems, form hypotheses, and drive analyses end-to-end.
• Excellent communication skills, with the ability to translate complex analytical findings into clear, actionable recommendations for non-technical stakeholders.
• Experience working in a fintech, payments, or digital lending environment.
• Familiarity with credit bureau data and alternative data sources.
• Experience with experimentation (A/B testing), champion-challenger frameworks, and test design.
• Exposure to machine learning-driven risk models and their application in production environments.
• Experience with BI/visualization tools (e.g., Tableau, Power BI, Looker) for dashboarding and reporting.
• Master's degree in a quantitative discipline is a plus.

Personal Attributes Desired:

• Data-driven, detail-oriented, and intellectually curious.
• Comfortable working in a fast-paced, evolving environment.
• Collaborative mindset with the ability to work effectively across functions and geographies.
• Ownership mentality and bias for action; able to drive initiatives from concept to execution.

LOCATION: San Jose, CA (Hybrid)


Job ID# 3599749


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