Head of Modeling

ClarityPay; New York (NY); Hybrid; USD 150,000 - 200,000; Full time

Benefits offered by this job

Competitive compensation

Comprehensive benefits

401k program

Job summary

ClarityPay is seeking a Head of Modeling to enhance decision science within the fintech sector, based in NYC or Atlanta, with the option for remote work. The role involves building an internal modeling team and managing end-to-end modeling across credit and fraud domains.

The ideal candidate will have over 8 years of experience in credit risk modeling, strong Python and SQL skills, and a deep understanding of regulatory landscapes. A competitive salary range of $150,000 to $200,000 is offered.

Qualifications

• 8+ years of experience in credit risk or decision-science modeling.
• Hands-on modeling experience with traditional and modern techniques.
• Familiarity with the fair-lending and regulatory landscape.

Responsibilities

• Build and lead the internal modeling team.
• Define and implement end-to-end credit/fraud modeling.
• Establish governance for model risk management.

Skills

Credit risk modeling

Decision science

Python

SQL

Model governance

Machine learning

Communication skills

Education

Advanced degree in a quantitative field

Job description

Overview

Head of Modeling to own and elevate the decision science at ClarityPay, a fintech redefining the point of sale credit market. Based in NYC or Atlanta (remote considered), the role leads the stand-up of a decision-science function with real data and momentum.

What you’ll own

• Build and lead the internal modeling team — define the team structure and operating model, hire your first internal modelers, and grow a high-caliber decision-science organization.
• End-to-end modeling across the credit and fraud lifecycle — application/underwriting scoring, behavioral and account-management models, line and limit assignment, risk-based pricing, loss forecasting, and collections/recovery optimization.
• Real-time decisioning at the point of sale — models and decision strategies that approve or decline in milliseconds, balancing approval rates, loss, fraud, and customer experience.
• Fraud and identity risk — first-party, third-party, synthetic identity, and account-takeover risk, in partnership with fraud and operations teams.
• Merchant- and channel-level risk — modeling and monitoring risk from the merchant side of the POS relationship.
• Model governance and risk management — documentation, validation practices, ongoing monitoring, and a framework aligned to model-risk-management expectations.
• Fair lending and regulatory rigor — disparate-impact and fair-lending testing, adverse-action reason codes and explainability, and collaboration with Legal/Compliance on ECOA/Reg B and related obligations.
• Data and infrastructure for modeling — partnering with Engineering and Data to build feature pipelines, deployment paths, and monitoring for reliable, maintainable models.

What you’ll build

Establish the foundation: a talented internal team and operating model, shared standards for model development and documentation, reproducible pipelines, validation and monitoring discipline, and governance to satisfy investors, funding partners, auditors, and regulators.

What we’re looking for

Required

• Substantial experience (typically 8+ years) building credit risk and/or decision-science models in lending, fintech, or banking, with meaningful time in consumer credit.
• Hands-on modeling background across traditional techniques (logistic regression, scorecards) and modern ML (gradient-boosted trees), with judgment to know when each is appropriate and to set high standards for a team.
• Strong Python and SQL, and fluency with the modern modeling and data stack.
• Experience with model governance, validation, monitoring, and a focus on documentation and reproducibility.
• Familiarity with the fair-lending and regulatory landscape for consumer lending (ECOA/Reg B, adverse action, model explainability, disparate-impact considerations).
• A track record of building and scaling a modeling or analytics team — hiring strong modelers, developing people, and setting technical standards and culture.
• The technical depth to set direction, evaluate work, and dive into detail when it matters.
• Ability to communicate complex modeling concepts clearly to executives, the board, and non-technical partners.

Preferred

• Direct experience in POS lending, BNPL, installment, or unsecured consumer credit.
• Fraud modeling experience (first-party, third-party, synthetic identity).
• MLOps / production deployment experience — feature stores, model serving, monitoring at scale.
• Exposure to capital markets or funding partners where loss models inform facility terms and reserves.
• Advanced degree in a quantitative field (statistics, economics, math, CS, or similar).

Who you are

We’ve described the technical bar above — but how you operate matters as well. You’re comfortable in a fast-paced startup, composed under pressure, and you lead by hiring, setting standards, and staying technically engaged while developing people.

What we offer

• Competitive fixed and variable compensation.
• Comprehensive benefits (medical, dental, vision).
• Collaborative office culture focused on clients and their customers.
• Opportunities to grow, lead, and shape the future of consumer finance.
• 401k program.

Role Details

• Preference for Atlanta or New York City; remote locations will be considered.
• Reports to the Chief Risk Officer.

Salary Range: $150,000 to $200,000, commensurate with experience and qualifications.

ClarityPay is an equal opportunity employer. We do not discriminate based on race, ethnicity, color, ancestry, national origin, religion, sex, sexual orientation, age, disability, veteran status, marital status, or any other legally protected status.