Why USAA?
At USAA, we are dedicated to empowering our members on their journey to financial security through competitive products, exceptional service, and trusted advice. We strive to be the premier choice for the military community and their families.
Join us at USAA, where our core values of honesty, integrity, loyalty, and service define our relationships with team members and our members. Be a part of something truly special and impactful.
The Opportunity
The Bank AI/ML team seeks to fill several Senior Data Scientist positions. We prefer candidates with backgrounds in model development for credit risk, marketing, or banking operations.
As a Senior Data Scientist, you will turn business challenges into actionable statistical, machine learning, simulation, and optimization solutions, generating valuable insights that drive automation, revenue growth, and risk reduction. You will collaborate with engineering teams to deliver scalable solutions and enhance customer-facing applications. Utilize your database, cloud, and programming skills to create analytical modeling solutions grounded in robust statistical and machine learning methodologies. Additionally, you will work with model risk management to validate models before deployment at scale.
This position is eligible for remote work within the continental U.S., with occasional travel. However, candidates within 60 miles of a USAA office will be expected to work on-site four days a week.
Relocation assistance is available for this position.
What you'll do:
- Gather, interpret, and manipulate structured and unstructured data to facilitate advanced analytical solutions for the business.
- Develop automated, scalable solutions using machine learning, simulation, and optimization methodologies to deliver impactful business insights.
- Select and implement appropriate modeling techniques based on data limitations, application needs, and business requirements.
- Create and deploy models within the Model Development Control (MDC) and Model Risk Management (MRM) frameworks.
- Write and assist peers in creating technical documentation to ensure knowledge retention, risk management, and technical reviews.
- Assess business needs and propose analytical projects to add value, prioritizing modeling and research efforts in conjunction with business and analytics leaders.
- Maintain a robust library of reusable, production-ready algorithms and code to ensure transparent, high-quality model development.
- Translate complex business requests into clear analytical questions, execute analyses or modeling, and effectively communicate results to non-technical stakeholders with a focus on actionable recommendations.
- Manage project milestones, identify risks and impediments, and escalate potential issues affecting project success.
- Develop best practices for collaboration with Data Engineering and IT to deploy analytical assets in alignment with modeling best practices and model risk management standards.
- Stay informed about cutting-edge techniques and actively seek opportunities to learn new technologies and methodologies.
- Mentor junior data scientists in modeling, analytics, and computer science tasks.
- Participate in internal communities focused on advancing data science technologies and fostering a collaborative culture.
- Ensure that risks related to business activities are identified, measured, monitored, and managed per risk and compliance policies.
What you have:
- Bachelor's degree in mathematics, computer science, statistics, economics, finance, actuarial sciences, or similar quantitative fields. Alternatively, 4 years of relevant experience may substitute for a degree.
- 6 years of experience in predictive analytics or data analysis, or an Advanced Degree (e.g., Master's, PhD) in a quantitative discipline with 4 years of experience.
- 4 years of experience in training and validating statistical, machine learning, and advanced analytics models.
- 4 years of experience using scripting languages (such as Python or R) for statistical analysis and building AI/ML models.
- Proven track record of writing clear, well-documented, and commented code (high code transparency).
- Strong experience in querying and preprocessing data from structured and unstructured databases using SQL, HQL, NoSQL, etc.
- Experience working with various data formats, including structured, semi-structured, and unstructured data files such as numeric, JSON/XML, text documents, images, etc.
- Skilled in performing ad-hoc analysis with descriptive, diagnostic, and inferential statistics.
- Ability to assess and communicate regulatory implications related to modeling efforts.
- Advanced knowledge of classical supervised modeling techniques such as regression, discriminant analysis, support vector machines, and decision trees.
- Advanced knowledge of unsupervised modeling techniques, including clustering algorithms like k-means and DBSCAN.
- Experience mentoring junior staff in technical