Credit Risk Analyst

Role Overview

This opportunity is posted for a partner organization that handles all applications and follow-up steps. The hiring company is seeking a Credit Risk Analyst located in the United States.

The position is central to a modern consumer lending operation, where analytical credit decisions directly affect access to responsible financing. In this role, you will study portfolio, segment, and vintage-level performance to identify patterns that inform underwriting rules, pricing decisions, and policy updates. The work requires strong quantitative thinking and has a direct influence on how the business balances growth with controlled risk.

You will assess approval rates, loss behavior, and model effectiveness while contributing to continuous improvements in credit decisioning systems. Because the role is embedded in a fast-moving fintech environment, you will work closely with stakeholders in risk, finance, product, and technology. It is well suited to someone who enjoys converting complex datasets into practical credit strategy. The broader mission is to support fairer and more transparent access to essential lending for everyday needs.

Key Accountabilities

• Review the effectiveness of credit policies by examining approval rates, decision distribution, cutoff performance, and tiering approaches.
• Track portfolio performance across segments, vintages, and cohorts, with attention to delinquency, default patterns, and origination quality.
• Evaluate the balance between approvals and losses to help shape risk appetite, profitability, and underwriting decisions.
• Support optimization of pricing and lending terms by analyzing APR structures, fees, and risk-adjusted product returns.
• Observe model and scorecard health using measures such as Gini, KS, and rank-order stability.
• Contribute to model validation, back-testing, and feature review efforts that strengthen model performance.
• Work across finance, collections, fraud, and technology teams to align metrics and support data-led decisions.

Requirements

• A bachelor’s degree in Finance, Economics, Statistics, Mathematics, Data Science, or another quantitative discipline.
• At least 3-5+ years of experience in credit risk analytics, underwriting analytics, or portfolio analytics, preferably in consumer lending.
• Advanced working knowledge of SQL and Python, or alternatively R, in a professional analytics setting.
• Hands-on experience with credit policy analysis, vintage analysis, approval-rate tracking, and/or loss forecasting.
• Familiarity with credit scorecards, model monitoring, and underwriting decision systems.
• Solid understanding of consumer lending products and core credit risk metrics.
• Exposure to A/B testing, experiments, or scenario analysis is strongly preferred.
• Strong analytical ability with the skill to turn findings into clear business recommendations.

Benefits and Additional Information

• Annual compensation is listed at $72,000 to $90,000.
• The position is fully remote within the United States.
• Employees receive flexible paid time off and 12 paid holidays.
• Medical, dental, and vision coverage are included, with up to 80% of premiums paid by the employer.
• Paid parental leave is provided.
• Coverage includes long-term disability and basic life insurance.
• A matching 401(k) retirement plan is available.
• The team environment is collaborative, fast-growing, and fintech-focused.
• The role offers the chance to contribute directly to financial access and responsible lending practices.

Hiring and Data Processing Notes

Applications are reviewed through an AI-assisted matching process designed to surface the most suitable candidates quickly and consistently against the role’s core requirements. The shortlist is then forwarded to the employer, who manages interviews, assessments, and all final hiring decisions.

By applying, you acknowledge that your personal data may be processed to evaluate your candidacy and shared with the hiring employer as needed for recruitment purposes. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws, including GDPR. You may request access, correction, deletion, or objection related to your data at any time.

The recruitment process may also use AI tools to assist with tasks such as resume review, application analysis, and identifying possible inconsistencies in submitted materials. These tools support the recruitment team but do not replace human judgment, and final hiring decisions are made by people.