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About the Role

Drive the strategic adoption and practical application of AI, particularly Generative AI, across USAA Federal Savings Bank. Identify and implement AI solutions to boost productivity, automate processes, reduce costs, and create new revenue streams within financial services. Scout and evaluate external AI tools and technologies to leverage innovative solutions, including intelligent work assistants to enhance employee experience and member value.

Responsibilities

Gathers, interprets, and manipulates structured and unstructured data to enable advanced analytical solutions.
Develops scalable, automated solutions using machine learning, simulation, and optimization.
Selects appropriate modeling techniques and technologies based on data limitations, application, and business needs.
Develops and deploys models within the Model Development Control (MDC) and Model Risk Management (MRM) framework.
Composes technical documents for knowledge persistence, risk management, and technical review.
Assesses business needs to propose and recommend analytical and modeling projects.
Works with business and analytics leaders to prioritize analytics and modeling problems/research efforts.
Builds and maintains a robust library of reusable, production-quality algorithms and supporting code.
Translates complex business requests into specific analytical questions, executes analysis/modeling, and communicates outcomes to non-technical colleagues.
Manages project milestones, risks, and impediments.
Escalates potential issues that could limit project success or implementation.
Develops best practices for engaging with Data Engineering and IT to deploy production-ready analytical assets.
Maintains expertise and awareness of cutting-edge techniques.
Actively seeks opportunities and materials to learn new techniques, technologies, and methodologies.
Serves as a mentor to junior data scientists in modeling, analytics, and computer science tasks.
Participates in internal communities that drive the maintenance and transformation of data science technologies and culture.
Ensures risks associated with business activities are effectively identified, measured, monitored, and controlled.

Requirements

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 may be substituted for a degree.
6 years of experience in predictive analytics or data analysis OR Advanced Degree (e.g., Master's, PhD) in a quantitative discipline and 4 years of experience in predictive analytics or data analysis.
4 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 languages (e.g., Python, R) for statistical analyses and/or building and scoring AI/ML models.
Proven experience writing clear, well-documented, and commented code.
Strong experience in querying and preprocessing data from structured and/or unstructured databases using languages like SQL, HQL, NoSQL.
Strong experience working with structured, semi-structured, and unstructured data files (e.g., delimited numeric data, JSON/XML, text documents, images).
Demonstrated skill in performing ad-hoc analytics using descriptive, diagnostic, and inferential statistics.
Ability to assess and articulate regulatory implications and expectations of distinct modeling efforts.
Advanced experience with classical supervised modeling concepts and technologies (e.g., linear/logistic regression, SVM, decision trees, forest models).
Advanced experience with unsupervised modeling concepts and technologies (e.g., k-means clustering, hierarchical clustering, DBSCAN).
Experience guiding and mentoring junior technical staff in business interactions and model building.
Experience communicating analytical and modeling results to non-technical business partners with emphasis on business recommendations and actionable applications.

Skills

AI
Generative AI
Machine Learning
Simulation
Optimization
Python
R
SQL
HQL
NoSQL
Descriptive Statistics
Diagnostic Statistics
Inferential Statistics
Supervised Modeling
Unsupervised Modeling

Location

Remote (Continental U.S.)
Hybrid (within 60-mile radius of a USAA office)

Work Type

Remote
Hybrid
On-site

Experience Level

6 years of experience in predictive analytics or data analysis
4 years of experience in predictive analytics or data analysis (with Advanced Degree)

Education Level

Bachelor's degree in a quantitative discipline
Master's degree
PhD

Salary/Compensations

$143,320-$273,930

Benefits

Comprehensive medical, dental and vision plans
401(k)
Pension
Life insurance
Parental benefits
Adoption assistance
Paid time off program with paid holidays
16 paid volunteer hours
Various wellness programs
Career path planning
Continuing education

About the Company

USAA's mission is to empower members to achieve financial security through competitive products, exceptional service, and trusted advice.
USAA seeks to be the #1 choice for the military community and their families.
Core values: honesty, integrity, loyalty, and service.
Proud to support active-duty military spouses with potential remote or hybrid flexibility.

Equal Opportunity

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.