Senior Data Scientist – Model Development

Requirements Must have:

• We require a bachelors degree in mathematics, computer science, statistics, economics, finance, actuarial science, science and engineering, or a comparable quantitative field; alternatively, we accept 4 additional years of relevant quantitative experience in place of a degree.
• We require 6 years of experience in predictive analytics or data analysis, or an advanced degree plus 4 years of relevant experience.
• We require 4 years of experience training and validating statistical, physical, machine learning, or other advanced analytics models.
• We require 4 years of experience using a dynamic scripting language such as Python or R for statistical analysis and AI/ML model development and scoring.
• We require proven ability to write clear, well-documented code with strong transparency and appropriate comments.
• We require strong experience querying and preparing data from structured and unstructured sources using SQL, HQL, No
  
  SQL, or similar query languages.
• We require strong experience working with structured, semi-structured, and unstructured data types, including delimited files, JSON/XML, text, and images.
• We require demonstrated capability in ad hoc analysis using descriptive, diagnostic, and inferential statistics.
• We require the ability to understand and explain the regulatory impacts and expectations tied to different modeling initiatives.
• We require advanced knowledge of classical supervised modeling methods such as linear/logistic regression, discriminant analysis, support vector machines, decision trees, and ensemble forest models.
• We require advanced knowledge of unsupervised techniques such as k-means, hierarchical clustering, neighbor-based methods, and DBSCAN.
• We require experience mentoring junior technical staff in both business-facing discussions and model development.
• We require experience presenting analytical and modeling findings to non-technical stakeholders with a focus on recommendations and practical business use.

• We prefer experience in a mid-sized or large banking environment.
• We prefer strong proficiency in Python and/or SAS.
• We prefer experience partnering with control functions and risk stakeholders.
• We prefer knowledge of Model Risk Management, Model Governance, and applicable regulatory requirements.

• We gather, interpret, and transform structured and unstructured data to support advanced analytical work.
• We design scalable, automated solutions using machine learning, simulation, and optimization to create business insight and measurable value.
• We choose suitable modeling approaches and technologies based on data constraints, use case, and business objectives.
• We develop and deploy models within our Model Development Control and Model Risk Management frameworks.
• We prepare technical documentation, and support peers in creating materials for knowledge retention, risk review, and technical validation.
• We assess business needs and recommend analytics and modeling initiatives that can deliver value.
• We partner with business and analytics leaders to rank and prioritize research and modeling efforts.
• We build and maintain reusable, production-ready algorithms and code libraries that support transparent, high-quality model development.
• We translate complex business requests into analytical questions, perform the analysis or modeling, and communicate findings to non-technical partners with clear recommendations.
• We manage milestones, risks, and blockers across projects, and elevate issues that may affect delivery or implementation.
• We establish best practices for working with Data Engineering and IT to deploy production-grade analytical assets aligned with modeling and risk standards.
• We stay current on emerging methods, tools, and techniques, and actively pursue learning opportunities.
• We mentor junior data scientists in modeling, analytics, and computer science tasks.
• We contribute to internal communities that help evolve our data science culture and technology landscape.
• We ensure business risks are identified, measured, monitored, and controlled in line with our compliance and risk policies.

We are USAA, an organization committed to helping our members achieve financial security through competitive products, exceptional service, and trusted guidance. Our values of honesty, integrity, loyalty, and service shape how we support one another and the military community we serve. We are hiring several Senior Data Science professionals for our Bank AI/ML team to help deliver applied machine learning solutions that drive automation, revenue growth, and risk reduction.

This is a remote-eligible role in the continental U.S. with occasional business travel; however, candidates living within 60 miles of a USAA office are expected to work on-site four days per week. Relocation assistance is available, and we offer comprehensive benefits including medical, dental, and vision coverage, 401(k), pension, life insurance, parental benefits, adoption assistance, paid time off with…