Partner with stakeholders to understand credit risk management requirements and translate them into data-driven solutions
Proactively identify and communicate challenges, opportunities, and risks associated with end-to-end model development and deployment life-cycle
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
Keep abreast with emerging trends in machine learning and identify opportunities to leverage new tools
Mentor and support junior data scientists, sharing knowledge and best practices to elevate the data science practice at WEX

4 or more years of professional experience in data science, machine learning, and artificial intelligence
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
Advanced knowledge of SQL and experience creating and managing large datasets
Advanced knowledge of Python or R and experience with common data science libraries such as lightgbm, scikit-learn, pandas
Deep understanding of model deployment requirements for scalable solutions
Deep expertise in statistical and machine learning techniques
Strong communication and presentation skills
Evidence of creative problem solving, critical thinking and a continual learning mindset in credit risk management

Senior Data Scientist

Key skills