Senior Fraud Data Scientist

WEX

Data Scientist optimizing risk solutions for WEX using machine learning. Partnering with stakeholders to build models and drive better decision-making.

Posted 6/10/2026full-timeRemote • 🇺🇸 United StatesSenior💰 $140,000 - $165,400 per yearWebsite

Tech Stack

Tools & technologies

PandasPythonScikit-LearnSQL

About the role

Key responsibilities & impact

Partner with stakeholders to understand credit risk management requirements and translate them into data-driven solutions to measure and monitor credit risk across the firm’s products and services.
Proactively identify and communicate challenges, opportunities, and risks associated with end-to-end model development and deployment life-cycle to ensure timely completion of the entire product.
Leverage advanced machine learning, artificial intelligence, and statistical methods and technologies to design flexible, scalable, and automated risk modeling solutions.
Develop and review code and automated processes to extract credit risk patterns from large scale application and transaction data, behavioral patterns, and other risk indicators.
Keep abreast with emerging trends in machine learning and identify opportunities to leverage new tools to solve problems and improve processes.
Mentor and support junior data scientists, sharing knowledge and best practices to elevate the data science practice at WEX.

Requirements

What you’ll need

4 or more years of professional experience in data science, machine learning, and artificial intelligence, with a focus on credit risk management in underwriting, behavioral surveillance, and loss prevention in the financial services industry.
Master’s or Ph.D. degree in a quantitative field such as Mathematics, Statistics, Data Science, Operations Research, Computer Science.
Strong knowledge of credit risk-drivers in small and medium sized businesses, public firms, and private firms, including data typically used in credit risk management from external credit bureaus and internal risk management processes
Advanced knowledge of SQL and experience creating and managing large datasets to organize and extract useful information
Advanced knowledge of Python or R and experience with common data science libraries such as lightgbm, scikit-learn, pandas, etc..
Deep understanding of model deployment requirements for scalable solutions and real-time feature stores
Deep expertise in statistical and machine learning techniques, including modeling, testing and inference, sampling methods, supervised and unsupervised learning.
Strong communication and presentation skills with an ability to relate complex analytics findings to business outcomes
Adaptable and comfortable working collaboratively and independently in a self-starting manner
Evidence of creative problem solving, critical thinking and a continual learning mindset in credit risk management.

Benefits

Comp & perks

health, dental and vision insurances
retirement savings plan
paid time off
health savings account
flexible spending accounts
life insurance
disability insurance
tuition reimbursement
quarterly or annual bonus based on role and applicable plan

ATS Keywords

✓ Tailor your resume

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

data sciencemachine learningartificial intelligencecredit risk managementSQLPythonRlightgbmscikit-learnpandas

Soft Skills

communication skillspresentation skillscreative problem solvingcritical thinkingadaptabilitycollaborationindependencementoringknowledge sharingcontinual learning

Certifications

Master’s degreePh.D. degree