• Providing advanced analytics, ML model design, technical leadership. • Collecting, analyzing and interpreting large data sets to identify trends, patterns, and provide key business insights. • Performs data mining, cleaning, and aggregation processes to prepare data, implement data models, conduct analysis, and develop databases. • Develops insights and reports from multiple structured and unstructured data sources using programming, statistical, and analytical techniques and tools. • Maintains continuous collaboration with teams to understand the underlying purpose, focus, and objective of each data analysis project to ensure alignment and support. • Designs, develops, and implements the most valuable data-driven solutions for the organization. • Works autonomously, but may provide a leadership role for the work group through knowledge in the area of specialization.

• Develop end‑to‑end NLP and GenAI solutions, including text classification, summarization, RAG systems, conversational AI, and document intelligence pipelines. • Build, fine‑tune, and evaluate LLM-based models using transformer architectures (BERT, GPT, T5, LLaMA, etc.). • Design and implement custom NLP workflows, embeddings, semantic search, vector databases, and prompt engineering strategies. • Develop scalable advanced ML models leveraging deep learning, traditional ML, and hybrid architectures. • Deploy models and AI apps using modern MLOps practices across cloud environments (Azure preferred). • Collaborate closely with product, engineering, and business teams to translate requirements into AI-driven solutions. • Monitor model performance, conduct error analysis, and continuously optimize pipelines.

• Partner directly with enterprise customers to understand business challenges, identify AI opportunities, and define solution requirements. • Lead customer engagements from discovery and solution design through deployment, adoption, and measurable business impact. • Serve as a trusted technical advisor, helping customers successfully implement and scale AI-driven solutions. • Present technical concepts, solution recommendations, and business outcomes to audiences ranging from practitioners to executive leadership. • Design, build, and deploy scalable machine learning, Generative AI, and agentic AI solutions for real-world supply chain challenges. • Develop production-ready ML pipelines, AI applications, prototypes, and proof-of-concepts. • Evaluate emerging AI technologies and adapt state-of-the-art techniques to customer and product needs. • Ensure solutions balance technical excellence, scalability, and business value. • Collaborate closely with Product, Engineering, Solutions Consulting, Sales, and Customer Success teams to deliver customer outcomes. • Influence product strategy by bringing customer insights, implementation learnings, and industry trends back into the organization. • Mentor team members and contribute to best practices in AI solution development and deployment.

• Serve as a primary facilitator for preparation, execution and follow up for all Planning, Programming, and Budgeting Committee – Guard (PPBC-G) forums (General Officer / Strategic Level forums), to include Resourcing Council of Colonels (RCoC), Resource Integration Steering Committee (RISC). • Coordinates across Army National Guard Bureau staffs to develop topics, products, and presentations for submission to the PPBC-G process. • Support the design, development, and execution of all data analytic efforts led by the GS-13 Data Scientist as directed by the DAG-R Division Chief/Deputy Division Chief in support of the Chief Financial Officer’s analytic agenda. • Provide expertise on ARNG Roles, Missions, Authorities and Army strategic guidance and key planning efforts such as The Army Plan (TAP), Total Army Analysis (TAA), the Army Equipment Modernization Strategy (AEMS), and the Long-Range Investment Requirements Analysis (LIRA). • Develop and enhance websites, applications, and secure access to databases based upon requirements for analytic efforts as approved by the COR.