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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # AI Data Scientist, Sr. - **Company:** Washington and Idaho Railway Inc - **Location:** San Antonio, TX, United States (Remote available) - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Amazon Web Services, Data Analysis, Cluster Analysis, Databases, Information Engineering, Data Systems, Python (Programming Language), Logistic Regression, Machine Learning, NoSQL, SQL Databases, Support Vector Machine, Unstructured Data, Cloud Platform System, Large Language Models, Multi-Agent Systems, Prompt Engineering, Google Vertex AI, Generative AI, Agentic-AI, Information Technology, Optimization Algorithms, Machine Learning Operations, K Means - **Published:** October 11, 2026 - **Apply:** https://arc.dev/remote-jobs/j/redirect/pqpeodt3c5 ## About the Role * Bachelor's degree in Mathematics, Computer Science, Statistics, Science, Engineering, or a related quantitative field, or equivalent experience (4+ years). * 6+ years of experience in predictive analytics or data analysis, or an advanced degree (Master's or PhD) with 4+ years of relevant experience. * Proven experience in training and validating advanced analytics models, including statistical, physical, and machine learning models (4+ years). * Expertise in Python programming for statistical analysis and AI/ML model development and scoring (4+ years). * Strong skills in querying and preprocessing data from structured and unstructured databases using SQL, HQL, NoSQL, or similar languages. * Demonstrated ability to perform ad-hoc analytics with descriptive, diagnostic, and inferential statistics, considering real-world constraints. * Knowledge of regulatory implications and experience in the statistical validation of models for risk management. * Advanced understanding of classical supervised modeling techniques such as linear/logistic regression, support vector machines, decision trees, and ensemble models. * Experience with unsupervised modeling methods like k-means clustering, hierarchical clustering, and density-based algorithms. * Expertise in large language models and agentic systems development using frameworks such as LangChain, VertexAI, or MCP, including prompt engineering and multi-agent systems. * Experience with MLOps practices for deploying AI solutions in cloud environments like AWS or GCP. * Strong communication skills to convey complex analytical findings to non-technical stakeholders and guide junior team members. ## Description We are seeking a highly skilled AI Data Solutions Scientist to join our innovative Data Science team within the Technology organization at USAA. In this role, you will collaborate across functions with architecture, engineering, and product teams to transform operations and enhance member experiences through advanced analytics and AI solutions. Your work will involve tackling a broad spectrum of business challenges by leveraging structured and unstructured data, utilizing traditional operations research techniques such as simulation, optimization, and machine learning, as well as cutting-edge technologies including generative AI, large language models, and agent frameworks. As a key member of our forward-thinking community, you will contribute to the development of next-generation AI models, shaping the future of AI at USAA. The position offers a flexible work environment requiring presence in the office four days a week and can be based in San Antonio, TX, Plano, TX, or Phoenix, AZ, * Gather, interpret, and manipulate structured and unstructured data to enable advanced analytical solutions aligned with business objectives. * Develop scalable, automated models using machine learning, simulation, and optimization techniques to generate actionable insights. * Select appropriate modeling techniques considering data limitations, application requirements, and business needs. * Develop and deploy models within the Model Development Control (MDC) and Model Risk Management (MRM) frameworks, ensuring compliance and quality standards. * Create and review technical documentation for knowledge sharing, risk management, and technical validation purposes. * Assess business needs to recommend analytical projects that add value and prioritize research efforts accordingly. * Collaborate with business and analytics leaders to identify key problems and develop innovative solutions. * Build and maintain a library of reusable, high-quality algorithms and supporting code to ensure transparency and reproducibility. * Translate complex business questions into analytical tasks, execute analyses, and communicate results with clear business implications. * Manage project milestones, identify risks, and escalate issues that could impact project success or implementation timelines. * Establish best practices for collaboration with Data Engineering and IT teams to deploy production-ready analytical assets. * Stay updated with the latest advancements in AI and data science techniques, actively seeking opportunities for continuous learning. * Mentor junior data scientists in modeling, analytics, and technical problem-solving to foster team growth. * Participate in internal communities to promote data science culture and technological innovation. * Ensure all activities comply with risk, compliance, and regulatory policies, effectively managing associated risks.