• Supports the development, optimization, and maintenance of data queries and analytics pipelines that power the Predictive Dairy Solutions platform. • Works within cross-functional teams consisting of business leaders, data scientists, dairy industry experts, and technology implementation specialists. • Responsible for writing, tuning, and managing SQL queries and data transformations that underpin dairy predictive algorithms and customer-facing analytics. • Must work with business stakeholders (internal and external). • Holds responsibility for ensuring data quality and compliance with established protocols for product implementation. • Requires strong capabilities in desktop manipulation of large, and sometimes complex, datasets. • Design, write, and optimize SQL queries that power dairy predictive algorithms and customer-facing platform analytics. • Support the deployment and lifecycle management of dairy analytics and predictive algorithms. • Perform data mapping and modeling exercises to translate business and scientific requirements. • Perform quality checks on available data to ensure completeness, internal consistency. • Collaborate with R&D and data science teams to support scientific innovation.

• Lead the strategy, roadmap, and execution for Data, Analytics, AI, Automation, and Innovation across the enterprise. • Establish enterprise data governance, architecture, engineering, analytics, and business intelligence capabilities that enable data-driven decision-making. • Lead AI strategy, governance, adoption, and value realization, including Generative AI, Agentic AI, Microsoft Copilot, Machine Learning, and Intelligent Automation. • Identify, prioritize, and deliver high-value AI and automation use cases that improve productivity, operational efficiency, customer experience, and business performance. • Evaluate and scale emerging technologies and innovation initiatives that support digital transformation and competitive advantage. • Partner with leaders across Architecture, Application Development, Infrastructure, IT Operations, and Cybersecurity to ensure alignment with enterprise technology strategies and modernization efforts. • Build and lead high-performing teams while fostering a culture of innovation, accountability, and continuous improvement. • Serve as a trusted advisor to executive leadership on technology-enabled business transformation and investment decisions. • Ensure compliance with security, privacy, governance, regulatory, and responsible AI requirements.

• Lead the design, development, testing, validation, and deployment of advanced analytics and machine learning solutions. • Manage analytics projects supporting fraud detection, fraud prevention, waste and abuse identification, and investigative activities. • Develop and evaluate predictive models, anomaly detection methods, risk models, and entity-resolution techniques. • Lead the development of analytics solutions using artificial intelligence, machine learning, natural language processing, graph analytics, and data visualization. • Identify and refine analytics use cases in collaboration with government stakeholders, investigators, and program teams. • Translate business, investigative, and operational requirements into technical analytics solutions. • Lead technical discovery, data assessment, feature development, model selection, and solution design activities. • Evaluate model performance, identify gaps, and recommend refinements or recalibration as needed. • Ensure analytics models and outputs are accurate, explainable, defensible, repeatable, and aligned with project objectives. • Track project progress, risks, issues, dependencies, and quality-control activities. • Conduct technical reviews and quality-control reviews of analytics work products before delivery. • Review code, models, documentation, data transformations, and analytic outputs for accuracy and completeness. • Support the deployment, monitoring, maintenance, and ongoing improvement of analytics models in production environments. • Collaborate with data engineers and data-management teams to support data ingestion, preparation, governance, quality, and lineage. • Develop and maintain technical documentation describing methodologies, data sources, model designs, assumptions, findings, and limitations. • Present analytical findings, technical recommendations, and project updates to technical and non-technical stakeholders. • Provide technical leadership, mentoring, and guidance to data scientists, analysts, and other project personnel.

• Partner with agency stakeholders to gather requirements and define analytics and reporting needs • Assess and prepare data from multiple systems for analytics and reporting use cases • Design and develop operational and decision-support dashboards that drive action • Translate program workflows and policy into clear metrics, KPIs, and reporting logic • Build and publish user-centered data products that are accessible and meaningful to business users • Advise stakeholders on opportunities to expand the role and impact of data across the agency • Collaborate across program, policy, and technical teams to align reporting with business priorities