Data Scientist

About The Company

USAA is a leading financial services organization dedicated to serving the military community and their families. Our mission is to empower our members to achieve financial security through highly competitive products, exceptional service, and trusted advice. We pride ourselves on maintaining core values of honesty, integrity, loyalty, and service, which guide our interactions with members and each other. USAA is committed to fostering an inclusive environment that supports active-duty military spouses and offers flexible work arrangements, including remote or hybrid options, to accommodate their needs. Our innovative approach and dedication to excellence make USAA a preferred choice within the financial industry and a trusted partner for those who serve.

About The Role

We are seeking a highly skilled AI Data Solutions Scientist to join our Technology organization at USAA. In this pivotal role, you will work within our dynamic Data Science team, collaborating closely with architecture, engineering, and product partners to revolutionize our operations and customer experiences. Your expertise will be instrumental in transforming vast amounts of structured and unstructured data into actionable insights that drive strategic decision-making and innovation. You will be at the forefront of developing scalable, automated solutions utilizing machine learning, simulation, optimization, and cutting-edge AI technologies, including generative AI, large language models, and multi-agent systems. This position offers a unique opportunity to contribute to the next generation of AI modeling at USAA, shaping the future of financial services for our members.

Qualifications

The ideal candidate will possess a bachelor’s degree in mathematics, computer science, statistics, engineering, or a related quantitative field, or equivalent experience. Candidates should have at least six years of experience in predictive analytics or data analysis, with advanced degrees (Master’s or PhD) preferred. Proven expertise in training and validating complex models, including machine learning, statistical, and physical models, is essential. Proficiency in Python for analysis and model development, along with strong SQL, NoSQL, and data querying skills, is required. Candidates must demonstrate experience in developing and deploying models within risk management frameworks, ensuring compliance with regulatory standards. Familiarity with classical supervised and unsupervised modeling techniques, as well as advanced knowledge of large language models, agent systems, and MLOps in cloud environments like AWS or GCP, is highly desirable. Excellent communication skills for translating technical findings into business insights, along with mentoring capabilities, are crucial for success in this role.

Responsibilities

• Gather, interpret, and manipulate both structured and unstructured data to enable advanced analytical solutions that support business objectives.
• Design, develop, and implement scalable, automated machine learning, simulation, and optimization solutions that generate actionable insights and deliver business value.
• Select appropriate modeling techniques and technologies based on data characteristics, application needs, and business requirements.
• Ensure models are developed and deployed within the Model Development Control (MDC) and Model Risk Management (MRM) frameworks, maintaining compliance and quality standards.
• Compose and review technical documentation for knowledge sharing, risk assessment, and technical validation purposes.
• Assess business needs to propose analytical and modeling projects that add measurable value, prioritizing initiatives with the greatest impact.
• Collaborate with business and analytics leaders to identify and prioritize key research and development efforts.
• Build and maintain a library of reusable, production-quality algorithms and supporting code, ensuring transparency and high data quality standards.
• Translate complex business questions into specific analytical tasks, execute analyses, and communicate findings effectively to non-technical stakeholders with actionable recommendations.
• Manage project milestones, identify risks, and escalate issues that could impact project success or deployment timelines.
• Develop best practices for engaging with Data Engineering and IT teams to deploy production-ready analytical solutions aligned with modeling and risk management standards.
• Stay current with emerging techniques and technologies in data science and AI, actively seeking opportunities for continuous learning and innovation.
• Mentor junior data scientists, fostering their growth and ensuring high standards of technical excellence.
• Participate in internal communities focused on advancing data science technologies and cultivating a data-driven culture within the organization.
• Ensure all activities comply with risk, compliance, and regulatory policies, effectively managing potential risks associated with business activities.

Benefits

USAA offers a comprehensive benefits package designed to support the physical, financial, and emotional well-being of our employees. Benefits include medical, dental, and vision coverage, a 401(k) plan, pension options, life insurance, parental leave, adoption assistance, and a paid time off program that includes holidays and volunteer hours. We also provide wellness programs, career development opportunities, and continuing education support to help employees achieve their professional goals. Our commitment to employee well-being and growth ensures a supportive and engaging work environment that values work-life balance and personal development.

Equal Opportunity

USAA is an Equal Opportunity Employer. We are committed to creating a diverse and inclusive workplace where all qualified applicants receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or protected veteran status. We believe in fostering a culture of respect and opportunity for everyone, ensuring fair treatment and equal access to all employment opportunities.