Senior Data Scientist

Posted 8ds ago

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Job Description

Data Scientist optimizing risk solutions and models for WEX. Collaborating with stakeholders and leveraging machine learning to enhance credit risk management.

Responsibilities:

  • 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:

  • 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:

  • health, dental and vision insurances
  • retirement savings plan
  • paid time off
  • health savings account
  • flexible spending accounts
  • life insurance
  • disability insurance
  • tuition reimbursement