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Why USAA? At USAA, our mission is to empower our members to achieve financial security through highly competitive products, exceptional service and trusted advice. We seek to be the #1 choice for the military community and their families.
Embrace a fulfilling career at USAA, where our core values - honesty, integrity, loyalty and service - define how we treat each other and our members. USAA roles may offer remote or hybrid flexibility for active-duty military spouses consistent with applicable policy and business needs.
The Opportunity
We are seeking a Lead AI Individual Contributor Data Scientist to drive the strategic adoption and practical application of AI, particularly Generative AI, across USAA Federal Savings Bank (USAA FSB). You will identify and implement AI solutions - whether cutting-edge industry advancements, existing solutions from other USAA lines of business, or tools that connect and integrate various platforms and IT systems - to boost productivity, automate processes, reduce costs, and create new revenue streams within the financial services context. This includes actively scouting for and evaluating external AI tools and technologies through various channels, such as professional networks and ties to academia, AI events, conferences, academic research, and a keen awareness of technological advancements, to ensure we are leveraging the most innovative solutions available.
These efforts will encompass exploring AI solutions that serve as intelligent work assistants, streamlining and optimizing routine tasks for our employees, ultimately enhancing the experience and value delivered to our USAA members, while also considering the visionary potential and ethical implications of these advancements. This role is remote eligible in the continental U.S. with occasional business travel. However, individuals residing within a 60-mile radius of a USAA office will be expected to work on-site four days per week.
Relocation assistance is available for this position.
What you'll do: Gathers, interprets, and manipulates complex 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.
Leads efforts to build and maintain a robust library of reusable, production-quality algorithms and supporting code, to ensure model development and research efforts are transparent and based on the highest quality data. Manages project portfolio milestones, risks, and impediments. Anticipates potential issues that could limit project success or implementation and escalates as needed.
Establishes and maintains best practices for engaging with Data Engineering and IT to deploy production-ready analytical assets consistent with modeling best practices and model risk management standards. Actively seeks opportunities and materials to learn new techniques, technologies, and methodologies. Serves as a mentor to data scientists in modeling, analytics, computer science, business acumen, and other 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 in accordance with risk and compliance policies and procedures. Bachelor’s degree in mathematics, computer science, statistics, economics, finance, actuarial sciences, science and engineering, or other similar quantitative discipline; 8 years of experience in a predictive analytics or data analysis OR Advanced Degree (e.g., Master’s, PhD) in mathematics, computer science, statistics, economics, finance, actuarial sciences, science and engineering, or other similar quantitative discipline and 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 one or more dynamic scripted language (such as Python, R, etc.) for performing statistical analyses and/or building and scoring AI/ML models.
Expert ability to write code that is easy to follow, well documented, and commented where necessary to explain
