Finance OPT Jobs in South Carolina

Date: Oct 27, 2026

Location: Greenville, SC, US, 29601

Company: Purpose Financial

Brand: Purpose Financial

Address: 322 Rhett Street, Greenville, South Carolina, United States - 29601

Purpose Financial, Inc. is an innovative consumer financial services company that offers a diverse suite of credit products, promoting financial inclusion and meeting consumers wherever they are. Through its brands, the company is committed to helping customers achieve their version of financial stability in the moment and in the future. Since 1997, Purpose Financial has been a pioneer in the consumer credit and financial services market offering money solutions in over 800 storefront locations and online lending. Providing services in over 23 states, Purpose Financial employs over 2,500 team members.

At Purpose Financial we are always on the lookout for motivated individuals who share in our values of mutual respect to join our team of outstanding professionals.

We offer:

• Competitive Wages
• Health/Life Benefits
• Health Savings Account plus Employer Seed
• 401(k) Savings Plan with Company Match
• Paid Parental Leave
• Company Paid Holidays
• Paid Time Off including Volunteer Time
• Tuition Reimbursement
• Business Casual Environment
• Rewards & Recognition Program
• Employee Assistance Program
• Office in downtown Greenville that offers free parking, onsite gym, free snacks/drinks

Position Summary

This position reports to the Director, Data Science and Credit Risk, and leads Purpose Financial's fraud risk analytics and strategy across the customer lifecycle, including application and origination, identity verification, funding, payments, and account servicing, in both store and online channels. The role is accountable for detecting, preventing, and measuring fraud such as third-party and synthetic identity fraud, first-party fraud and bust-out, payment fraud (ACH, debit card, and returned payments), and account takeover, while balancing loss reduction against approval rates, customer experience, and operational cost. This is a player-coach role: the incumbent remains hands-on with data, modeling, and strategy design while leading and developing a team of fraud analysts and data scientists. Because fraud and credit losses are closely linked, the role works side by side with the Credit Risk team to classify losses correctly, align decision strategies, and ensure fraud controls and credit policy work together. The position may be filled at the Manager or Senior Manager level depending on experience; the Senior Manager level carries broader ownership of the fraud strategy roadmap, a larger team, and greater executive-facing accountability.

Job Responsibility

• Own the development, implementation, and ongoing monitoring of fraud detection models (statistical and machine learning) and rules across the customer lifecycle, from application through funding, payments, and account servicing.
• Design and manage fraud decision strategies, including rules, model cutoffs, step-up identity verification, and manual review queues, balancing fraud losses against approval rates, false positives, and customer friction.
• Partner with Credit Risk to define and maintain fraud versus credit loss classification (e.g., first-payment default, never-pay, and confirmed-fraud tagging) so that models, loss reporting, and policy decisions rely on accurate performance labels.
• Monitor fraud KPIs such as fraud loss rate, attack rate, false-positive rate, review rate, and alert hit rate; build early-warning dashboards and alerting; and lead root-cause analysis on emerging attacks, fraud rings, and loss spikes.
• Identify and respond to evolving threats, including synthetic identities, AI-generated or altered documents, deepfake and biometric spoofing, bot-driven application attacks, and payment and ACH return abuse.
• Design and run test/control (champion/challenger) experiments to measure the impact of fraud strategies and to optimize decisions, verification steps, line assignment, and offer terms across products, channels, and customer segments.
• Evaluate, select, and manage third-party fraud data and tool vendors (identity verification, device and behavioral data, consortium data, bank account verification, and credit bureau fraud attributes), including retro testing, ROI analysis, and ongoing performance monitoring.
• Partner with Technology to implement models and rules in production decisioning systems, define data requirements, and ensure accurate, timely data pipelines and feature engineering.
• Work with Fraud Operations, Store Operations, and Customer Service to translate analytics into investigation workflows, queue prioritization, and front-line controls, and to capture investigation outcomes as feedback for model improvement.
• Ensure fraud models and strategies meet Model Risk Management standards and applicable consumer lending regulations, including model documentation, validation support, fair lending review, and adverse action requirements where fraud decisions affect applicants; coordinate with Compliance, Legal, and Internal Audit.
• Develop and maintain fraud prevention policies and procedures in partnership with Compliance and Operations.
• Hire, lead, coach, and develop a team of fraud analysts and data scientists; set priorities, review technical work, and uphold standards for code quality, reproducibility, and documentation.
• Prepare and present regular reporting on fraud trends, losses, and strategy performance to the Director, Data Science and Credit Risk, and senior leadership, translating technical findings into clear business recommendations.
• Build relationships with industry peers, consortiums, and fraud networks to stay current on fraud trends and prevention techniques.
• Senior Manager level: Own the multi-year fraud strategy and roadmap, recommend fraud loss and risk appetite targets to leadership, lead a larger team (which may include leads or managers), and represent the fraud function with executives, auditors, and examiners.
• Perform ad-hoc analysis and other duties as assigned.

Education Required

Equivalent Education Level Required: Bachelor’s Degree in a quantitative field (Engineering, Statistics, Mathematics, Economics, Computer Science, or another comparable quantitative field) required. Master’s Degree or PhD in a quantitative field preferred.

Experience Required

• Manager: 5+ years of experience in fraud analytics, fraud strategy, or risk data science, preferably in consumer lending, fintech, or payments, including at least 2 years leading or mentoring analysts or data scientists.
• Senior Manager: 8+ years of experience in fraud analytics, fraud strategy, or risk data science, including at least 4 years of people management and demonstrated ownership of a fraud strategy or fraud loss outcomes at an enterprise level.
• Experience in subprime or near-prime consumer lending preferred.

Knowledge Required

• Advanced proficiency in SQL and Python (or R) for data manipulation, analysis, and modeling.
• Hands-on experience building, deploying, and monitoring fraud models using machine learning techniques (e.g., gradient boosting, anomaly detection, graph/network analysis), including handling class imbalance and delayed or noisy fraud labels.
• Direct experience in data quality, ELT, and feature engineering for fraud identification, including identity, device, velocity, and payment-behavior features.
• Deep knowledge of consumer lending fraud typologies (synthetic and stolen identity, first-party fraud and bust-out, account takeover, payment and ACH fraud) and the controls used to mitigate them.
• Experience with fraud and identity data vendors, consortium data, and decision engines or rules platforms.
• Solid understanding of experimental design and statistical principles (hypothesis testing, p-values, statistical power, causal inference).
• Working knowledge of model risk management and regulatory expectations in consumer lending, such as FCRA, ECOA/Regulation B, adverse action, fair lending, data privacy, and information security.
• Understanding of how fraud and credit risk interact, including loss classification and its effect on credit models, pricing, and loss forecasting.
• Proven leadership skills, with the ability to hire, develop, and manage a high-performing team.
• Excellent written and verbal communication skills, including the ability to translate complex analysis into clear recommendations for non-technical audiences.
• Ability to work independently and manage multiple projects in a dynamic, high-volume, fast-paced environment; adaptable to change.
• Ability to understand and ensure compliance with policies, procedures, and laws governing our industry, business, and products.
• Ability to interact professionally and to develop and maintain business relationships across the organization and with external partners.
• Ability to quickly learn all technology needed to perform the role; experience with cloud data platforms and version control (e.g., Git) preferred.

Physical Requirements

Sitting for long periods of time; standing occasionally; walking; bending; squatting; kneeling; pushing/pulling; reaching; twisting; frequent lifting of less than 10 lbs., occasional lifting of up to 20 lbs.; typing; data entry; grasping; transferring items between hands and/or to another person or receptacle; use of office equipment to include computers; ability to travel to, be physically present at, and complete the physical requirements of the position at any assigned location.

Competencies

Travel

0-10%

Attire

Business Casual

Other

Must be eligible to work in the USA and able to pass a background check.

All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, or disability.

Requisition ID: 46781

Nearest Major Market: Greenville

Nearest Secondary Market: South Carolina