IT-SLE Operations Analyst

Serves as the bridge between business intelligence, data analysis, advanced analytics, and innovative AI solutions, incorporating AI into daily analytical processes and decision-making for operational teams. Performs data analysis and modeling to identify trends, patterns, opportunities, and solutions to operational and business problems, while leveraging artificial intelligence tools, automation, and advanced analytics to improve data exploration, statistical models, generate actionable insights, and support decision-making.

This position leverages the practical integration of AI into existing operational workflows.

Assess and Identify Areas of Opportunity for AI

• Identify the standard operational workflows, systems, and processes for an operational team and assess opportunities where AI may support efficiencies in workflow, data collection, analysis, and decision-making.
• Assess operational workflows, systems, and analytical processes to identify inefficiencies and opportunities for AI, automation, and process improvement, reducing manual effort, improving turnaround time, or enhancing analytical consistency.
• Perform ad hoc and recurring data analysis and modeling to address operational questions, identify trends and patterns, evaluate performance, and support decision‑making.
• Collect, prepare, evaluate, and analyze data from multiple sources to identify opportunities, assess operational performance, and develop actionable insights.
• Meet with operational partners to determine feasibility of applying AI‑assisted tools (e.g., copilots, large language models, automated analytics) to support data exploration, modeling, insight generation, and analytical efficiency.

Develop and Implement AI Solutions

• Partner with analysts to introduce AI‑enabled methods into standard analytical practices.
• Translate business questions into AI‑assisted analytical approaches, including natural‑language querying, statistical analysis, model interpretation, pattern detection, and predictive or other analytical modeling.
• Prototype and test AI‑enabled analytical methods that augment existing reporting, dashboards, and analysis workflows.
• Develop low‑code or no‑code automations within existing software that streamline routine data preparation, analysis, and reporting tasks.
• Apply and interpret statistical, mathematical, or predictive models, as appropriate, to support operational planning, evaluation, forecasting, and decision‑making.
• Collaborate with data engineers or platform teams to operationalize repeatable analytical processes.
• Validate AI outputs for accuracy, bias, and relevance before use in decision‑making.
• Integrate AI-supported reporting, trend detection, anomaly identification, and analytical modeling to support dashboards, reports, and ad‑hoc analyses.

Communication and Stewardship of AI Solutions

• Collaborate with stakeholders to explain AI‑supported insights, analytical findings, and modeling results in clear, non‑technical language.
• Serve as a resource for responsible AI use, helping analysts understand appropriate use cases and limitations.
• Follow organizational standards for data governance, privacy, and responsible AI use.
• Document AI‑assisted workflows, analytical methodologies, modeling assumptions, and sources to ensure transparency and reproducibility.
• Stay informed on emerging AI tools and techniques relevant to data analysis and modeling, recommending adoption when value‑aligned.
• Supports technical projects as part of a project team.
• Evaluate internal systems for efficiency, problems, and inaccuracies.
• Performs related work as required

• Bachelor’s degree in information technology, business administration, data analysis or related field, and six years…