Data Science Manager: Credit Risk & Modeling Leader

Established in 2018, Clicklease is dedicated to empowering small business owners frequently overlooked by traditional lenders. Our headquarters are located in the vibrant city of West Valley City, UT, with operations extending to Radial, Alajuela, Costa Rica. We’ve cultivated a dynamic environment where equipment financing goes beyond being a mere service; it acts as the gateway to realizing entrepreneurial dreams.Our Core Values:

1. We Are A Happy Company:
At Clicklease, happiness is not just a byproduct; it’s a fundamental value. Join a workplace where positivity and joy are cultivated, creating an environment where you can bring your best self to work every day.

2. We Celebrate Collective Intelligence:
We thrive on the brilliance of collaboration. Clicklease is a space where diverse minds come together, combining their intelligence to create solutions that matter. Your ideas are not just heard; they’re celebrated.

3. We Practice Empathy:
Empathy isn’t just a word in our dictionary; it’s a daily practice. Join a team that values understanding and compassion. At Clicklease, we recognize the human side of business and foster a culture where empathy is a guiding principle.

4. We Listen & Learn:
Growth is a continuous journey  believe in listening and learning from one another. Your insights and experiences contribute to our collective knowledge, making us stronger as a team.

At Clicklease, we have a clear purpose - to fulfill the capital needs of underserved entrepreneurs and their Main Street Businesses. We achieve this mission through simple, fast, and innovative equipment leasing solutions. This is not just a statement; it’s the driving force behind everything we do.

About the role

The Data Science Manager owns the development, deployment, and lifecycle management of Clicklease’s credit, fraud, and portfolio models, translating business problems into production-ready modeling solutions that drive measurable risk and financial outcomes.

What you’ll be doing:

• Lead end-to-end development and lifecycle management of credit, fraud, and portfolio models, including PD, LGD, CNL/CGL forecasts, BAV cash flow scoring, fraud/identity scoring, and collections/recovery models
• Serve as hands-on technical lead on the most complex and highest-impact modeling projects, setting standards for experimental rigor, feature engineering, validation methodology, and documentation
• Manage, mentor, and develop the Data Science team, including performance management, coaching, hiring, and prioritization
• Own model governance across the portfolio, including documentation, validation artifacts, backtesting, challenger frameworks, and drift monitoring
• Partner with Data Engineering to design and maintain feature store architecture, training/serving pipelines, and data quality standards
• Translate business questions from Credit Risk, Collections, Finance, Operations, and Sales into well-scoped modeling projects and executive-ready recommendations
• Drive evaluation and adoption of new data sources and modeling techniques to improve decisioning quality
• Ensure compliance with fair lending, ECOA/FCRA, adverse action, and internal model risk standards

Essential Functions

• Design, develop, validate, and deploy predictive models that directly impact credit, fraud, and portfolio performance
• Lead and maintain model governance practices, including monitoring, backtesting, and compliance validation
• Manage and develop team members, including hiring, coaching, and performance evaluation
• Translate complex analytical outputs into actionable business recommendations for senior stakeholders
• Ensure adherence to regulatory requirements, including fair lending and adverse action compliance
• Design and evaluate experimentation frameworks (A/B/C/D tests, pricing tests, strategy rollouts) with proper statistical rigor and causal inference
• Represent the Data Science function in executive and cross-functional forums, translating technical outcomes into business impact

Minimum Requirements

• 7+ years of experience in data science, machine learning, or quantitative modeling
• 2+ years of experience leading projects or mentoring data scientists
• Experience building and…