AI Analyst

JOB SUMMARY

Support the transition from traditional dashboards and reporting toward AI-enabled analytics. The AI Analyst combines AI tooling with operations domain expertise to provide decision support, automate recurring analytical work, and deliver reliable insight from operational data.

• Decision support: Conduct root‑cause analysis, benchmarking, and ad‑hoc investigations in support of operations stakeholders. Apply AI tooling to reach well‑supported conclusions more efficiently than conventional analysis alone.
• Data ingestion and curation: Load operations data into analytical systems, identify and address anomalies, and enrich records with domain context through AI‑assisted workflows.
• Automation: Automate recurring data preparation, reporting, and analysis tasks. Convert repeated ad‑hoc requests into self‑service tools.
• AI tooling application: Apply the AI systems, agents, and templates developed by Operations Analytics to deliver insight vide structured feedback to inform ongoing improvements.
• Prompt and configuration tuning: Refine prompts and agent configurations to optimize recurring analytical workloads for accuracy, cost, and performance.
• Reporting: Prepare clear, well‑supported analytical and technical reports for operations stakeholders that are rigorous enough to inform decisions and accessible enough to act upon.

• Bachelor's Degree in Management Information Systems, Computer Sciences, Accounting, Finance, Business Administration, or other related field with specific job‑related experience as follows:

• Minimum 3 years in an analytical role (e.g., operations analyst, data analyst, process engineer, reliability engineer).
• Proficient in SQL and Python, including pandas, notebook environments, and current business intelligence tools.
• Hands‑on experience applying LLM‑based tools to analytical work beyond general‑purpose querying.
• Operations domain knowledge, including an understanding of the distinction between raw instrument readings and validated operational data.
• Clear, concise technical writing suited to operations and engineering audiences.

• Direct midstream experience in pipelines, plants, measurement, hydraulics, or integrity.

• Turnaround time on ad‑hoc operations analysis requests.
• Proportion of recurring analyses automated and transitioned to self‑service.
• Quality of curated data delivered to downstream users, measured by user feedback and error rates.
• Contributions to prompt and agent configuration improvements that benefit shared AI tools across the team.

Primary users and partners are operations teams across ONEOK. Collaborates with the Data Steward on the delivery of clean, contextualized data; with the AI Engineer on tooling improvements; and with Forward Deployed Engineers on embedded analytical needs within strategic teams.

• Skills in relational database design including table structures, indexes and primary/foreign key fields.
• Skills in use and function of office equipment including computers and applicable software.
• Skills in interacting, advising and communicating effectively.
• Skills in developing solutions to complicated issues using abstract thinking in new or complex situations.
• Skills in managing and prioritizing multiple assignments with competing deadlines.
• Skills in reading and interpreting correspondence, reports, production statistics, cost analyses, contracts, accounting statements, income statements, ledgers, manuals and legal documents.
• Ability to develop information, conduct meetings and present information to individuals and groups.
• Ability to apply math, algebra, statistical and volumetric methods.
• Ability to be self‑motivated and self‑directed.
• Ability to influence and facilitate discussions across a wide range of teams and technologies.
• Ability to mentor less experienced personnel on complex technologies.

• None required

• Sedentary Work
  - Exerting up to 10 pounds of force occasionally (Occasionally: activity or condition exists up to 1/3 of the…