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. Be part of what truly makes us special and impactful.
The Opportunity
The Data Scientist Lead will work closely with the Data Science Director to ensure that AI/ML modeling solutions are successfully developed and implemented. This will involve supervising multiple projects/initiatives, providing technical expertise, ensuring quality results, and mentor and leading Senior and Junior Data Scientists.
Through cross-team collaboration, the lead works to understand business problems to formulate and coordinate AI/ML solutions in the Consumer Lending, Bank Operations, and Automation space. A Lead Data Scientist is expected to have a consulting mentality and be a subject matter expert in model building, communication, and leadership.
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. 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, to ensure model development and research efforts are transparent and based on the highest quality data.
- Assists team with translating business request(s) into specific analytical questions, executing analysis and/or modeling, and communicating outcomes to non-technical business colleagues with a focus on business action and recommendations.
- 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.
- Interacts with internal and external peers and management to maintain expertise and awareness of cutting-edge techniques. 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.
What you have:
- Bachelor’s degree in mathematics, computer science, statistics, economics, finance, actuarial sciences, science and engineering, or other similar quantitative discipline; OR 4 years of experience in statistics, mathematics, quantitative analytics, or related experience (in addition to the minimum years of experience required) may be substituted in lieu of degree.
- 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 do