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.

As a dedicated Data Scientist Lead, you will translate business problems into applied statistical, machine learning, simulation, and optimization solutions to inform actionable business insights and drive business value through automation, revenue generation, and expense and risk reduction. In collaboration with engineering partners, delivers solutions at scale, and enables customer-facing applications. The person will use database, cloud, and programming knowledge to build analytical modeling solutions using statistical and machine learning techniques. Collaborates with other data scientists to improve USAA’s tooling, expanding the company’s library of internal packages and applications. The incumbent will work with model risk management to validate the results and stability of models before being pushed to production at scale.

We offer a flexible work environment that requires an individual to be in the office 4 days per week. This position can be based in one of the following locations: San Antonio, TX, Plano, TX, Phoenix, AZ, Colorado Springs, CO, Charlotte, NC or Tampa, FL. 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 using 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 clear and based on the highest quality data.
• Assists team with translating business request(s) into specific analytical questions, driving analysis and/or modeling, and presenting outcomes to non-technical business colleagues with a focus on business action and recommendations.
• Leads project portfolio achievements, risks, and impediments. Anticipates potential issues that could limit project success or implementation and escalates as needed.
• Establishes and maintains standard methodologies 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 innovative 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, eye for business, and other social 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, supervised, 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 field; 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 subject area 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 multifaceted scripted language (such as Python, R, etc.) for performing statistical analyses and/or building and scoring AI/ML models.
• Experienced ability to write code that is easy to follow, well documented, and commented where necessary to explain logic (high code clarity).
• Strong experience in querying and preprocessing data from structured and/or unstructured databases using query languages such as SQL, HQL, NoSQL, etc.
• Strong experience in working with structured, semi-structured, and unstructured data files such as delimited numeric data files, JSON/XML files, and/or text documents, images, etc.
• Excellent demonstrated skill in performing ad-hoc analytics using descriptive, diagnostic, and inferential statistics.
• Proven ability to assess and articulate regulatory implications and expectations of distinct modeling efforts.
• Project management experience that demonstrates the ability to anticipate and appropriately lead project achievements, risks, and impediments. Demonstrated history of appropriately communicating potential issues that could limit project success or implementation.
• Expert level experience with the concepts and technologies associated with classical supervised modeling for prediction such as linear/logistic models, discriminant analysis, support vector machines, decision trees, forest models, etc.
• Expert level experience with the concepts and technologies associated with unsupervised modeling such as k-means clustering, hierarchical/agglomerative clustering, neighbors algorithms, DBSCAN, etc.
• Demonstrated experience in guiding and mentoring junior technical staff in business interactions and model building.
• Demonstrated ability to communicate ideas with team members and/or business leaders to convey and present very technical information to an audience that may have little or no understanding of technical concepts in data science.
• A consistent track record of communicating results, insights, and technical solutions to Senior Executive Management (or equivalent).
• Extensive technical skills, consulting experience, and business savvy to collaborate with all levels and subject areas within the organization.

What sets you apart:

• Extensive model building experience (preferably in banking) covering a variety of AI/ML and traditional statistical modeling approaches.
• Extensive hands-on experience preparing data and code for modeling.
• Experience with the entire model lifecycle, including conceptualization, development, implementation, validation, and ongoing performance monitoring.
• Experience working directly with clients, customers, or internal business partners.
• Experience leading client or customer relationships and expectations, including senior leadership.

Compensation range: The salary range for this position is: $164,780 - $314,960.

USAA does not provide visa sponsorship for this role. Please do not apply for this role if at any time (now or in the future) you will need immigration support (i.e., H-1B, TN, STEM OPT Training Plans, etc.).

Compensation: USAA has an effective process for assessing market data and establishing ranges to ensure we remain competitive. You are paid within the salary range based on your experience and market data of the position. The actual salary for this role may vary by location.

Employees may be eligible for pay incentives based on overall corporate and individual performance and at the discretion of the USAA Board of Directors.

The above description reflects the details considered necessary to describe the principal functions of the job and should not be construed as a detailed description of all the work requirements that may be performed in the job.

Benefits: At USAA our employees enjoy best-in-class benefits to support their physical, financial, and emotional wellness. These benefits include 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, and various wellness programs. Additionally, our career path planning and continuing education assists employees with their professional goals.

For more details on our outstanding benefits, visit our benefits page on USAAjobs.com.

Applications for this position are accepted on an ongoing basis, this posting will remain open until the position is filled. Thus, interested candidates are encouraged to apply the same day they view this posting.

USAA is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran.