Lead Data Scientist

5 days ago


Charlotte, North Carolina, United States USAA Full time
Job Title: Lead Data Scientist - Fraud Identity Analytics

At USAA, we are committed to facilitating the financial security of our members and their families. As a Lead Data Scientist - Fraud Identity Analytics, you will play a critical role in developing and implementing quantitative solutions to improve our ability to detect and prevent identity theft, account takeover, and first-party/synthetic fraud.

Key Responsibilities:
  • Develop and implement machine learning models to detect and prevent identity theft and account takeover
  • Collaborate with cross-functional teams to design and implement graph database solutions to identify and prevent financial crimes
  • Work with data engineering teams to deploy production-ready analytical assets consistent with modeling best practices and model risk management standards
  • Partner with business leaders to identify business needs and propose analytical and modeling projects to generate business value
  • Lead efforts to build and maintain a robust library of reusable, production-quality algorithms and supporting code
Requirements:
  • Bachelor's degree in mathematics, computer science, statistics, economics, finance, actuarial sciences, science and engineering, or other similar quantitative field
  • 8 years of experience in predictive analytics or data analysis
  • 6 years of experience in training and validating statistical, physical, machine learning, and other advanced analytics models
  • 4 years of experience in one or more dynamic scripted language (such as Python, R, etc.) for performing statistical analyses and/or building and scoring AI/ML models
What We Offer:
  • Competitive salary and benefits package
  • Opportunities for professional growth and development
  • Collaborative and dynamic work environment
  • Recognition and rewards for outstanding performance

USAA is an EEO/AA Employer - applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, age, disability, genetic information, sexual orientation, gender identity or expression, pregnancy, protected veteran status or other status protected by law.


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