Credit Risk Manager

Greenbox Capital; Northern (KY); Remote; USD 130,000 - 165,000; Full time

Benefits offered by this job

Fully remote within the U.S.

Flexible PTO

Full benefits package

Collaborative teammates

Job summary

Greenbox Capital is seeking a Credit Risk Manager (US Remote) to lead analytics, predictive modeling, and portfolio insights that drive growth and credit performance. The role focuses on building robust risk frameworks and measurable improvements.

You will own credit decisioning frameworks, offer strategies, and verification approaches, partnering with the VP of Credit Risk & Analytics to optimize approvals, manage risk, and scale operations.

Qualifications

• Bachelor’s degree in mathematics, statistics, economics, finance, or a related field required; advanced degree preferred.
• 5–10 years of experience in credit risk analytics, preferably in small business lending, non-prime, or high-risk environments.
• 2+ years of leadership experience managing and developing teams.
• Proven success building or enhancing modern credit decisioning frameworks.
• Demonstrated impact driving business outcomes through analytics and modeling.

Responsibilities

• Drive decisioning frameworks and analytics to optimize approval strategy and portfolio outcomes.
• Own model performance optimization and business impact.
• Develop data strategy and vendor evaluation to integrate high-value sources.
• Collaborate across underwriting, finance, and product with actionable insights.
• Lead and develop a team within the Risk Analytics function.

Skills

SQL

Python

Excel

Statistical modeling

Education

Bachelor’s degree in mathematics, statistics, economics, finance, or related field

Tools

Snowflake

Databricks

BI tools

Job description

Credit Risk Manager - (US Remote)

Why this Role Matters:

The Credit Risk Manager serves as a key operator within Greenbox Capital’s credit organization, using analytics, predictive models, and portfolio insights to drive business growth and credit performance.

This role owns and evolves core credit strategies including offer strategy, portfolio management strategy, and verification strategy. The individual partners closely with the VP of Credit Risk & Analytics to optimize approval outcomes, manage portfolio risk, improve funnel performance, and support scalable growth.

The ideal candidate brings strong credit risk and portfolio management experience, deep familiarity with predictive modeling and decision science concepts, and the ability to translate analytics into practical business decisions. This role does not require a pure data scientist, but does require someone who can effectively leverage data science capabilities to improve credit and business outcomes.

This role reports to the VP of Credit Risk & Analytics and leads a team within the Risk Analytics function.

What Success Looks Like:

Here’s how your time might break down (actual time can shift depending on business needs):

• Decisioning Frameworks & Analytics – Driving approval strategy, segmentation, and portfolio optimization
• Model Performance & Optimization – Improving model accuracy and business impact
• Data Strategy & Vendor Evaluation – Identifying and integrating high-value data sources
• Cross-Functional Impact – Supporting underwriting, finance, and product with actionable insights

How you’ll be measured:

• Portfolio Management
  • Manage portfolio performance through segmentation, cohort analysis, and strategy refinement
  • Evaluate portfolio trends and risk concentrations to proactively adjust credit strategies
  • Balance approval growth with portfolio quality and return objectives

• Decisioning Framework Ownership:
  • Build and continuously improve credit decisioning frameworks that drive approval strategy, pricing, and portfolio outcomes
  • Own and optimize offer strategy across acquisition channels, customer segments, and risk tiers
  • Drive portfolio management strategies balancing growth, credit quality, and profitability
  • Develop and refine verification strategies to improve fraud detection, identity validation, and operational efficiency
  • Monitor approval funnels and conversion performance to identify opportunities for growth optimization

• Model Performance & Business Impact:
  • Evaluate and refine model performance using business KPIs, improving predictive accuracy and decision quality

• Cross-Functional Influence & Execution:
  • Partner effectively across teams to translate analytics into clear, actionable business decisions

You’re a Strong Fit if You:

• Demonstrate strong analytical thinking and can solve complex credit risk problems using data
• Have proven leadership ability, including managing and developing high-performing teams
• Thrive in fast-paced, ambiguous environments and can prioritize effectively
• Communicate clearly, translating technical findings into business recommendations
• Are highly organized with strong attention to detail and ownership mindset
• Show curiosity and continuously seek to improve systems, models, and outcomes
• Adapt well in a global, distributed team environment and collaborate effectively across functions

What You’ve Done Before:

• Bachelor’s degree in mathematics, statistics, economics, finance, or a related field required; advanced degree preferred
• 5–10 years of experience in credit risk analytics, preferably in small business lending, non-prime, or high-risk environments
• 2+ years of leadership experience managing and developing teams
• Proven success building or enhancing modern credit decisioning frameworks
• Demonstrated impact driving business outcomes through analytics and modeling

Tools and Expertise You’ll Bring:

• Strong proficiency in SQL, Python, and Excel
• Solid understanding of statistical modeling and model performance evaluation techniques
• Experience working with large datasets and credit decisioning systems
• Familiarity with modern data platforms (e.g., Snowflake, Databricks) and BI tools
• Strong understanding of credit underwriting processes, policy design, and segmentation strategies

What to Expect from Our Interview Process

We believe in a respectful, efficient, and transparent hiring experience. Here’s what you can expect (subject to changes depending on role):

Step 1: Initial Phone Screen (30 minutes)

Step 2: Hiring Manager Interview (1 hour)

Step 3: Interview with CEO

Step 4: Onsite Interview with Leadership

Step 5: Offer & Background Check

What's In It For You:

• Competitive Pay - We know your worth and we pay accordingly.
• Flexible PTO - Work hard, rest well. Take the time you need to recharge.
• Remote - Fully remote within the U.S., working Eastern Time hours to keep everyone aligned.
• Full Benefits Package - Health, dental, vision, 401K with employer match
• Smart, Supportive Teammates - Collaborate with sharp minds who are kind, driven and uphold our core values: Wear Green First, Pull the Thread, Move the Needle, Courage Over Comfort, Think Bold, Win Together, and Own the Outcome