AI Data Scientist

Experteer Overview In this AI Data Scientist role, you apply advanced analytics to structured and unstructured data to drive business insights and value. You’ll develop scalable ML, simulation, and optimization solutions within a robust risk and production framework, collaborating with Data Engineering, IT, and business teams. You’ll push the frontier of AI at USAA, balancing innovation with governance and risk management. This position offers hybrid flexibility and the chance to impact how the military community experiences financial security. Compensation / Benefits * Gather, interpret, and manipulate data to enable advanced analytics * Develop scalable ML, simulation, and optimization solutions to deliver business value * Choose appropriate modeling techniques aligned with data and business needs * Develop and deploy models within MDC and MRM frameworks * Prepare technical documents for knowledge management and risk review * Identify business needs and propose analytic projects to add value * Prioritize analytics and modeling efforts with analytics leaders * Build a library of reusable, production-grade algorithms and code * Translate business requests into analytical questions and communicate outcomes to non-technical stakeholders * Collaborate with Data Engineering, IT, and business partners to deploy production-ready analytics assets * Stay current with cutting-edge techniques and pursue learning opportunities * Identify, measure, monitor, and control risks per risk and compliance policies Tasks * Bachelor’s degree in mathematics, Computer Science, Statistics, Science, Engineering, or quantitative field, or 4 years of relevant education/experience; or advanced degree with 2+ years of predictive analytics experience * 2+ years of experience training and validating statistical, ML, or other advanced analytics models * 2+ years of Python for statistical analysis or ML model development * Experience writing clean, well-documented code with clear logic explanations * Experience querying/preprocessing data from structured/unstructured sources using SQL, HQL, NoSQL, etc. * Experience with descriptive, diagnostic, and inferential statistics and real-world constraints (latency, cost, reliability) in AI solutions * Experience with supervised modeling (linear/logistic regression, decision trees, SVMs, etc.) and unsupervised methods (k-means, clustering, DBSCAN) * Experience communicating analytical results to non-technical stakeholders with actionable recommendations * Experience with cloud environments and producing production-ready AI solutions Key requirements * comprehensive medical, dental, and vision plans * 401(k) * pension * life insurance * parental benefits * paid time off with holidays + 16 volunteer hours

add value * Prioritize analytics and modeling efforts with analytics leaders * Build a library of reusable, production-grade algorithms and code * Translate business requests into analytical questions and communicate outcomes to non-technical stakeholders * Collaborate with Data Engineering, IT, and business partners to deploy production-ready analytics assets * Stay current with cutting-edge techniques and pursue learning opportunities * Identify, measure, monitor, and control risks per risk and compliance policies Tasks * Bachelor’s degree in mathematics, Computer Science, Statistics, Science, Engineering, or quantitative field, or 4 years of relevant education/experience; or advanced degree with 2+ years of predictive analytics experience * 2+ years of experience training and validating statistical, ML, or other advanced analytics models * 2+ years of Python for statistical analysis or ML model development * Experience writing clean, well-documented code with clear logic explanations

• Experience querying/preprocessing data from structured/unstructured sources using SQL, HQL, NoSQL, etc. * Experience with descriptive, diagnostic, and inferential statistics and real-world constraints (latency, cost, reliability) in AI solutions * Experience with supervised modeling (linear/logistic regression, decision trees, SVMs, etc.) and unsupervised methods (k-means, clustering, DBSCAN) * Experience communicating analytical results to non-technical stakeholders with actionable recommendations * Experience with cloud environments and producing production-ready AI solutions Key requirements * comprehensive medical, dental, and vision plans * 401(k) * pension * life insurance * parental benefits * paid time off with holidays + 16 volunteer hours