This role pays more than
70%
of similar roles. Most pay
$155,075–$217,700
— the shaded band above.
At the midpoint, this role pays about
$209k
versus about
$186k
for comparable roles.
Based on 240 similar postings.
Employer
About USAA
USAA (United Services Automobile Association) is a San Antonio-based Fortune 500 financial services company founded in 1922, dedicated to providing insurance, banking, and investment solutions exclusively to U.S. military members, veterans, and their families.
USAA currently has
14 open roles
on FindRole.
Listed pay typically runs
$143,320–$273,930
across 14 roles with salary data.
As a Senior AI Data Scientist – Solutions Developer within the Technology organization, you will join the Data Science team to transform operations and experiences through advanced analytics. You will gather, interpret, and manipulate structured and unstructured data to build scalable, automated solutions using machine learning, simulation, and optimization techniques. Your daily work involves developing and deploying models within specific risk management frameworks while maintaining a library of production-quality algorithms. You will utilize Python, SQL, HQL, and NoSQL to perform statistical analysis and manage complex data pipelines. The role emphasizes cutting-edge technologies including generative AI, large and small language models, and agentic systems using frameworks like LangChain or VertexAI. You will solve complex business problems by translating technical results into actionable recommendations for non-technical stakeholders while mentoring junior staff in a highly regulated financial services environment.
Gather and manipulate structured and unstructured data to develop advanced analytical solutions for the business.
Build scalable, automated models using machine learning, simulation, optimization, and generative AI technologies.
Develop and deploy models within the Model Development Control (MDC) and Model Risk Management (MRM) frameworks.
Translate complex technical results into actionable recommendations for non-technical business stakeholders.
Maintain a library of reusable, production-quality algorithms and high-quality code to ensure transparency.
Mentor junior data scientists in modeling, analytics, and computer science tasks.
Collaborate with engineering teams to deploy production-ready analytical assets in cloud environments.
What we're looking for
Bachelor's degree in a quantitative field and 6+ years of experience in predictive analytics or data analysis; OR an advanced degree and 4+ years of experience.
4+ years of experience training and validating statistical, physical, machine learning, and other advanced analytics models.
4+ years of experience using Python for statistical analysis and building or scoring AI/ML models.
Strong experience querying and preprocessing data from structured and unstructured databases using SQL, HQL, NoSQL, or similar languages.
Advanced experience with supervised modeling (e.g., regression, decision trees) and unsupervised modeling (e.g., k-means clustering).
Expertise in LLMs and agentic systems development including prompt engineering, RAG, and frameworks like LangChain or VertexAI.
Experience with MLOps integration to facilitate production-scaled AI solutions in cloud environments such as AWS or GCP.
Experience communicating technical results to non-technical partners and mentoring junior staff (preferred); experience in highly regulated industries (preferred).