Data Scientist Senior

USAA•San Antonio, NC

37d•Hybrid

About The Position

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. We are proud to support active-duty military spouses. USAA roles may offer remote or hybrid flexibility for active-duty military spouses consistent with applicable policy and business needs. The Opportunity As a Senior Data Scientist, you will leverage advanced analytics, machine learning, and AI-driven solutions to transform complex financial and operational data into actionable business insights that influence key strategic decisions. Partnering closely with senior Finance leaders and cross-functional stakeholders, you will develop innovative forecasting and predictive modeling solutions that drive performance, support risk management, and create measurable business value. This is a highly visible opportunity to solve complex challenges at scale while contributing directly to the success of the CFO organization. We are seeking a collaborative and intellectually curious professional with an advanced degree (Master's or Ph.D.) in Mathematics, Economics, Statistics, Finance, Data Science, Actuarial Science, or a related quantitative field. The ideal candidate will bring a strong foundation in economic forecasting, statistical analysis, predictive modeling, and advanced analytics, along with expertise in Python, R, and Snowflake. Experience within a large financial services, banking, insurance, or consulting environment is highly desirable. In addition to building and deploying sophisticated analytical solutions, you will serve as a trusted advisor to senior leaders, translating complex model insights, forecast results, and risk implications into clear, actionable recommendations. This role offers the opportunity to influence data science best practices, mentor emerging talent, and thrive in a culture that values innovation, continuous learning, and strategic impact. 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 not available for this position.

Requirements

Bachelor's degree in Mathematics, Computer Science, Statistics, Economics, Finance, Actuarial Science, Science, Engineering, or quantitative field; OR 4 years of relevant education and/or experience.
6 years of experience in 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 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 language (such as Python, R, etc.) for performing statistical analyses and/or building and scoring AI/ML models.
Proven experience writing code that is easy to follow, well documented, and commented where necessary to explain logic (high code transparency).
Strong experience in querying and preprocessing data from structured and/or unstructured databases using query languages such as SQL, HQL, NoSQL, etc.
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 the concepts and technologies associated with classical supervised modeling for prediction such as linear/logistic regression, discriminant analysis, support vector machines, decision trees, forest models, etc.
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 of results.

Nice To Haves

Master's degree or Ph.D. in Mathematics, Economics, Statistics, Finance, Data Science, Actuarial Science, or a related quantitative discipline.
Strong quantitative foundation with demonstrated experience in economic forecasting, statistical analysis, predictive modeling, and advanced analytical techniques.
Advanced programming and data engineering skills, including proficiency in Python, R, and Snowflake, with experience developing, automating, and maintaining analytical and forecasting solutions.
Experience within a large financial services, banking, insurance, or consulting organization, supporting complex financial, risk management, forecasting, or regulatory initiatives.
Proven ability to analyze large and complex datasets, develop actionable insights, and apply quantitative methodologies to solve strategic business challenges.
Strong executive presence with the ability to communicate model insights, forecast results, and risk implications to senior leadership and key stakeholders.
Exceptional written and verbal communication skills, with a demonstrated ability to translate complex technical concepts and analytical findings into clear, concise, and actionable recommendations for executive, business, and regulatory audiences.
Familiarity with regulatory expectations, model governance frameworks, and risk management practices within highly regulated financial institutions.

Responsibilities

Gathers, interprets, and manipulates structured and unstructured data to enable advanced analytical solutions for the business.
Develops scalable, automated solutions using machine learning, simulation, and optimization to deliver business insights and business value.
Selects 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 assists peers with composing, technical documents for knowledge persistence, risk management, and technical review audiences.
Assesses business needs to propose/recommend analytical and modeling projects to add business value.
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, to ensure model development and research efforts are transparent and based on the highest quality data.
Translates complex business request(s) into specific analytical questions, executes on the analysis and/or modeling, and then communicates outcomes to non-technical business colleagues with focus on business action and recommendations.
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 consistent with modeling best practices and model risk management standards.
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 in accordance with risk and compliance policies and procedures.