The Role Develop machine learning and statistical models to identify, measure, and manage credit and fraud risk. Partner with stakeholders to translate requirements into scalable solutions, analyze large application and transaction datasets, deploy end-to-end models, and improve risk decision-making. The role requires advanced Python or R and SQL skills, expertise in fraud and underwriting models, model deployment, statistical methods, and mentoring junior data scientists. Summary Generated by Built In The Global Risk Solutions and Strategy group is a fast-growing team optimizing risk solutions and models, and we are a key function to help enable WEX's strategic objectives. The Risk Solutions Team employs data science methodologies (machine learning and statistical frameworks), a wide suite of data types, and modern technologies to develop solutions to inform decision making. Our team helps the firm identify and measure credit and fraud risk to proactively manage the risk throughout the client's life-cycle. As such, you will not only be working with the latest data and machine learning technologies and algorithms, you will be working in a dynamic environment alongside our stakeholders and domain experts to build models and drive better decision-making. About the Team/Role Partner with stakeholders to understand fraud risk management requirements and translate them into data-driven solutions to measure and monitor fraud 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 fraud 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. How you'll make an impact

Insights Driven:

Clear hypothesis and objective driven analytics that help drive our business decisions and ongoing metrics

Stakeholder Aligned:

Understand the needs and audience for deliverables with a succinct and tailored message to maximize impact

Results Focused:

Rigorous focus on how analytics drive the end to end experiences with clear path to production and measurable impact

Dynamic Collaboration:

Drive continual improvement of our team best practices and processes to power collaboration

Quality Mindset:

Trust in our findings is critical so data and analytic quality is understood and accounted for from the beginning Curiosity and Learnin g: Learn new technologies and collaborate and teach others how to use them as necessary.

Experience You'll Bring:

4 or more years of professional experience in data science, machine learning, and artificial intelligence, with a focus on fraud 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 fraud risk-drivers in small and medium sized businesses, public firms, and private firms, including data typically used in fraud 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.

How you will stand out:

Prior experience mentoring experience of data scientists Prior roles responsible for building underwriting and behavioral models. Knowledge of external intelligence sources, including third-party data providers e.g. LexisNexis, Socure, Dun and Bradstreet Experience using cloud environments to develop advanced models, such as AWS Sagemaker Experience with end-to-end machine learning systems and MLOps framework AI Tool Experience Preferred -- Gemini, ChatGPT, Similar The base pay range represents the anticipated low and high end of the pay range for this position. Actual pay rates will vary and will be based on various factors, such as your qualifications, skills, competencies, and proficiency for the role. Base pay is one component of WEX's total compensation package. Most sales positions are eligible for commission under the terms of an applicable plan. Non-sales roles are typically eligible for a quarterly or annual bonus based on their role and applicable plan. WEX's comprehensive and market competitive benefits are designed to support your personal and professional well-being. Benefits include health, dental and vision insurances, retirement savings plan, paid time off, health savings account, flexible spending accounts, life insurance, disability insurance, tuition reimbursement, and more. For more information, check out the "About Us" section.

Pay Range:

$140,000.00 - $165,400.00 Read Full Description Skills Required Four or more years of professional experience in data science, machine learning, and artificial intelligence, focused on fraud risk management in financial services Master's or Ph.D. degree in Mathematics, Statistics, Data Science, Operations Research, Computer Science, or a related quantitative field Strong knowledge of fraud risk drivers and data used in fraud risk management, including external credit bureaus and internal risk processes Advanced SQL knowledge and experience creating and managing large datasets Advanced Python or R knowledge and experience with data science libraries such as LightGBM, scikit-learn, and pandas Deep understanding of scalable model deployment requirements and real-time feature stores Deep expertise in statistical and machine learning techniques, including modeling, testing, inference, sampling, supervised learning, and unsupervised learning Strong communication and presentation skills, including the ability to connect analytics findings to business outcomes Ability to work collaboratively and independently in a self-starting manner Creative problem-solving, critical thinking, and continual learning mindset in credit risk management Experience mentoring data scientists Experience building underwriting and behavioral models Knowledge of external intelligence sources and third-party data providers such as LexisNexis, Socure, and Dun & Bradstreet Experience using cloud environments such as AWS SageMaker to develop advanced models Experience with end-to-end machine learning systems and MLOps frameworks Experience with AI tools such as Gemini or ChatGPT WEX Inc. Compensation & Benefits Highlights The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about WEX Inc. and has not been reviewed or approved by WEX Inc.. About This Summary Leave & Time Off Breadth — Leave offerings are portrayed as a standout, with generous PTO and additional paid time for volunteering. Time-off flexibility is also positioned as a meaningful part of the overall rewards experience. Retirement Support — Retirement benefits are presented as strong, including a 401(k) match that is described as competitive. This element appears to materially strengthen the total rewards package even when cash compensation feels less compelling. Strong & Reliable Incentives — Variable compensation is sometimes framed positively through bonuses and uncapped earning potential in sales-oriented roles. Stock options are also cited as an additional reward component that can improve perceived total compensation. Learn more about WEX Inc.'s Compensation & Benefits → WEX Inc. Insights What's It Like to Work at WEX Inc.? WEX Inc. Culture & Values WEX Inc. Career Growth & Development What's the Work-Life Balance Like at WEX Inc.? WEX Inc. Leadership & Management WEX Inc. Company Growth, Stability & Outlook View all jobs at WEX Inc. View WEX Inc. Profile Report Job