Credit Policy & Decisioning Analyst

Reach Financial•New York, NY

10h•$120,000 - $150,000•Remote

About The Position

Reach Financial is a FinTech platform helping people outsmart debt for good. We are building innovative products and best-in-class support that enable our customers to take control of their debt and de-mystify their personal finances. Our products and tools empower our customers to turn their financial goals into a reality. Reach Financial launched in 2015 and has helped our customers pay off over $1 billion in debt. We offer debt consolidation loans and personal loans; together, these markets represent a $1.5T opportunity. In time, we will expand beyond these products to offer solutions for a variety of our customers' personal finance challenges. We are a fast-growing and fast-paced FinTech startup with the stability of an established firm. You will have a front-row seat at a rapidly growing company innovating the FinTech industry. About the Department: Reach Financial’s Risk and Decision Science team consists of a group of Data Scientists and Analytics Professionals covering all the lending products. We are passionate about data and cutting-edge technology. Our goal is to leverage the data to drive the business growth agenda. The Risk and Decision Science team works cross functionally with other business units to ideate, hypothesize, analyze and test, formalize, implement, maintain, and track progresses for all initiatives. Role Summary: We are seeking a highly technical, detail-oriented, and extremely organized Credit Policy & Decision Engine Analyst to drive the implementation, testing, and optimization of credit policies within our decisioning platform (e.g., Taktile). This role sits with Risk department with primary responsibility for translating policy into scalable decision logic, system workflows, and data-driven rules. The ideal candidate has hands-on experience with decision engines or rule-based systems, strong analytical skills, and a proven ability to produce clear, structured, audit-ready documentation. You will partner closely with Product Engineering, Compliance and Capital Markets to ensure credit strategies are accurately implemented, rigorously tested, and continuously optimized.

Requirements

Bachelor’s degree in a quantitative or technical field (e.g., Data Science, Finance, Engineering, Analytics, Operations and business)
3–5 years of experience in fintech, lending, credit risk, or decision systems
Strong hands-on experience with: Rule-based systems, decision engines, or workflow platforms
Translating business logic into technical decision rules
Highly detail-oriented, extremely organized, with a strong focus on accuracy and control
Proven ability to produce clear, structured, and comprehensive documentation
Strong analytical and problem-solving skills with ability to work with complex datasets and logic
Experience with decision engines such as Taktile or rule-based systems
Strong understanding of decision logic, workflows, and conditional rules (if/then logic)
Experience with testing (UAT, scenario testing, validation frameworks)
Ability to analyze system outputs and troubleshoot issues across data and logic layers
Strong documentation discipline (SOPs, rule definitions, testing artifacts)
SQL for querying and validating decision outcomes
Experience with APIs, JSON, or system integrations
Python for analysis or automation
Technical execution & systems thinking
Exceptional attention to detail
Strong organizational and documentation skills
Analytical problem solving
Process discipline and control mindset
Cross-functional collaboration (Risk, Product, Engineering)
Ownership and accountability

Nice To Haves

Unsecured lending (personal loans, BNPL, credit cards, LOC)
Credit bureau data, underwriting logic, and risk segmentation
Lending operations, credit risk, or fintech environments
Exposure to loan origination systems or fintech platforms

Responsibilities

Translate credit policies into structured decision rules (eligibility, approval/decline, pricing, workflows)
Configure, maintain, and optimize decision logic in Taktile or similar rule-based platforms
Conduct scenario testing, UAT, and rule validation to ensure accurate system behavior
Analyze and troubleshoot decisioning issues across rule logic, data inputs, and system workflows
Monitor decision engine outputs (approvals, declines, routing, exceptions) for accuracy and consistency
Partner with Product Engineering teams on data integrations, APIs, and system enhancements
Maintain detailed change logs, test artifacts, and audit documentation for all rule updates
Support execution and refinement of credit policies for unsecured lending
Review policy exceptions, edge cases, and manual decision flows
Track performance metrics (approval rates, decline reasons, delinquencies, exceptions)
Identify and escalate policy gaps, data inconsistencies, or operational inefficiencies
Create and maintain high-quality, structured documentation (SOPs, decision trees, rule logic, workflows)
Ensure all policies and decision logic are clearly documented, version-controlled, and audit-ready
Support internal audits, controls, and governance requirements