Fraud​/Credit Data Scientist, Risk Solutions

About The Team/Role

The Global Risk Solutions and Strategy group is a fast‑growing team that optimizes risk solutions and models, helping WEX execute its strategic objectives. The team employs data‑science methodologies, a wide suite of data types, and modern technologies to develop solutions that inform decision‑making. Our work helps identify and measure credit, collections, and fraud risk to proactively manage risk throughout the client lifecycle, collaborating with stakeholders and domain experts to build models and drive better decisions.

You are a data scientist who excels at identifying solutions with machine learning and artificial intelligence models. You effectively assess how to best address a problem, recognizing where machine learning and AI fit within a broader strategy. You value strong communication, relationships, and are adept at mitigating risks and opportunities using advanced models.

• Learn from stakeholders and leaders how to connect a business problem to data‑driven solutions to measure and monitor risk across the firm’s products and services.
• Leverage advanced statistical and machine‑learning methods and technologies to design flexible, scalable, and automated modeling solutions.
• Develop code and automated processes to combine and transform large volumes of data from disparate sources, extracting informative patterns.
• Keep abreast of emerging trends in machine learning and identify opportunities to leverage new tools to solve problems and improve processes.
• Synthesize findings into actionable insights and articulate them to the appropriate stakeholders.
• Proactively identify and communicate challenges, opportunities, and risks associated with project work to ensure timely completion of the entire product.

• Insights Driven:
  Clear, hypothesis‑driven analytics that help guide business decisions and ongoing metrics.
• Stakeholder Aligned:
  Understand the needs and audience for deliverables, delivering succinct and tailored messages to maximize impact.
• Results Focused:
  Rigorous focus on how analytics drive end‑to‑end experiences with a clear path to production and measurable impact.
• Dynamic
  
  Collaboration:
  
  Drive continual improvement of team best practices and processes to power collaboration.
• Quality Mindset:
  Trust in findings is critical; data and analytic quality are understood and accounted for from the beginning.
• Curiosity and Learning:
  Learn new technologies and teach others how to use them as necessary.

• 1 to 3 years of hands‑on experience in data science, machine learning, or artificial intelligence, preferably in fintech or financial services.
• Excellent analytical, creative problem‑solving, and critical thinking skills, with the ability to tackle complex challenges and deliver innovative solutions.
• Master’s or Ph.D. degree in a quantitative field such as Mathematics, Statistics, Data Science, Operations Research, or Computer Science.
• Advanced knowledge of SQL and experience creating and managing large datasets to organize and extract useful information.
• Working knowledge of Python or R and experience with data science libraries such as Light
  
  GBM, scikit‑learn, pandas, Num Py, etc.
• 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.

• Prior experience building machine‑learning risk models in payment processing.
• Knowledge of data attributes and coverage of risk‑factors for credit, fraud, or other risk domains.
• Experience using cloud environments to develop advanced models, such as AWS Sage Maker.
• Experience with end‑to‑end machine‑learning systems and MLOps framework.

Pay Range: $ - $.

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. WEX’s compensation package is designed to support personal and professional well‑being.

Base pay is one component of the total compensation package. Non‑sales roles are typically eligible for a quarterly or annual bonus based on the role and applicable plan.