Senior Fraud Data Scientist

This is a fully remote position, open to applicants in United States.

📋 Description

• Collaborate with stakeholders to grasp credit risk management needs and convert them into data-driven solutions for assessing and monitoring credit risk across the firm’s offerings.

• Anticipate and articulate challenges, opportunities, and risks tied to the complete model development and deployment life cycle to ensure the timely delivery of the entire product.

• Utilize advanced machine learning, artificial intelligence, and statistical methodologies to create adaptable, scalable, and automated risk modeling solutions.

• Create and evaluate code and automated procedures to extract credit risk patterns from extensive application and transaction data, behavioral trends, and other risk indicators.

• Stay updated on emerging trends in machine learning and pinpoint opportunities to employ new tools for problem-solving and process enhancement.

• Guide and assist junior data scientists by sharing knowledge and best practices to enhance the data science capabilities at WEX.

⛳️ Requirements

• Minimum of 4 years of professional experience in data science, machine learning, and artificial intelligence, specifically focused on credit risk management in underwriting, behavioral surveillance, and loss prevention within the financial services sector.

• Master’s or Ph.D. in a quantitative discipline such as Mathematics, Statistics, Data Science, Operations Research, or Computer Science.

• Strong understanding of credit risk factors in small and medium-sized businesses, as well as public and private firms, including data commonly utilized in credit risk management from external credit bureaus and internal risk management processes.

• Advanced proficiency in SQL and experience in creating and managing large datasets to systematically extract valuable insights.

• Advanced expertise in Python or R along with experience using popular data science libraries such as lightgbm, scikit-learn, pandas, etc.

• Comprehensive knowledge of model deployment requirements for scalable solutions and real-time feature stores.

• In-depth proficiency in statistical and machine learning techniques, encompassing modeling, testing, inference, sampling methods, as well as supervised and unsupervised learning.

• Excellent communication and presentation skills with the capability to connect intricate analytics findings to business outcomes.

• Flexible and comfortable working both collaboratively and independently in a self-starting environment.

• Demonstrated creative problem-solving skills, critical thinking, and a commitment to continuous learning in credit risk management.

🏝️ Benefits

• 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