USAA-posted about 1 year ago
$158,960 - $286,130/Yr
Full-time • Senior
Remote • San Antonio, TX
Credit Intermediation and Related Activities

The Data Scientist Lead for Generative AI at USAA is responsible for translating complex business problems into actionable statistical and machine learning solutions. This role involves collaborating with engineering partners to deliver scalable solutions, enhancing internal tools, and ensuring model validation and risk management. The position requires a strong focus on mentoring junior data scientists and engaging with business leaders to identify analytical needs that drive business value.

  • Gathers, interprets, and manipulates sophisticated structured and unstructured data to enable advanced analytical solutions for the business.
  • Leads and conducts advanced analytics leveraging machine learning, simulation, and optimization to deliver business insights and achieve business objectives.
  • Guides team on selecting the appropriate modeling technique and/or technology with consideration to data limitations, application, and business needs.
  • Develops and deploys models within the Model Development Control (MDC) and Model Risk Management (MRM) framework.
  • Composes and peer reviews technical documents for knowledge persistence, risk management, and technical review audiences.
  • Partners with business leaders from across the organization to proactively identify business needs and proposes/recommends analytical and modeling projects to generate business value.
  • Works with business and analytics leaders to prioritize analytics and highly complex modeling problems/research efforts.
  • Leads efforts to build and maintain a robust library of reusable, production-quality algorithms and supporting code.
  • Assists team with translating business requests into specific analytical questions, executing analysis and/or modeling, and communicating outcomes to non-technical business colleagues.
  • Manages project portfolio milestones, risks, and impediments, anticipating potential issues that could limit project success or implementation.
  • Establishes and maintains best practices for engaging with Data Engineering and IT to deploy production-ready analytical assets.
  • Interacts with internal and external peers and management to maintain expertise and awareness of groundbreaking techniques.
  • Serves as a mentor to data scientists in modeling, analytics, computer science, and interpersonal skills.
  • Participates in enterprise-level efforts to drive the maintenance and transformation of data science technologies and culture.
  • Ensures risks associated with business activities are effectively identified, measured, monitored, and controlled.
  • Bachelor's degree in mathematics, computer science, statistics, economics, finance, actuarial sciences, or a similar quantitative field; OR 4 years of relevant experience may substitute for a degree.
  • 8 years of experience in predictive analytics or data analysis OR an advanced degree with 6 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 a dynamic scripted language (e.g., Python, R) for statistical analyses and AI/ML model building.
  • Expert ability to write clear, well-documented code.
  • Strong experience in querying and preprocessing data from various databases using SQL, HQL, NoSQL, etc.
  • Strong experience with structured, semi-structured, and unstructured data files.
  • Excellent skill in performing ad-hoc analytics using descriptive, diagnostic, and inferential statistics.
  • Proven track record to assess regulatory implications of modeling efforts.
  • Project management experience demonstrating the ability to manage milestones, risks, and impediments.
  • Expert level experience with classical supervised modeling concepts and technologies.
  • Expert level experience with unsupervised modeling techniques.
  • Experience in guiding and mentoring junior technical staff.
  • Experience in developing Generative AI.
  • Experience in Cloud Computing.
  • Advanced Python skillsets.
  • Sophisticated experience in Machine Learning and Deep Learning Modeling techniques.
  • Experience in deploying Data Science models into business solutions.
  • Experience in working with diverse teams including business stakeholders, IT, project management, legal, and compliance.
  • Experience in mentoring and developing junior data scientists.
  • Experience in Life Insurance sales organizations, underwriting organizations, and/or call center support.
  • Comprehensive medical, dental, and vision plans
  • 401(k)
  • Pension
  • Life insurance
  • Parental benefits
  • Adoption assistance
  • Paid time off program with paid holidays plus 16 paid volunteer hours
  • Various wellness programs
  • Career path planning and continuing education assistance
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