AI Analytics Engineer — Hybrid, Power BI & FinOps

Vizient, Inc.

Chicago (IL)

Hybrid

USD 77,000 - 135,000

Full time

8 days ago

Application generator

Turn this role into an interview — a resume and cover letter built around what this employer wants.

Get past ATS filters

Benefits offered by this job

Incentive eligible

Comprehensive benefits

Job summary

Vizient, Inc. is seeking a data analytics professional to support measurement, reporting, and operational intelligence for its enterprise AI program. You will transform AI platform usage, adoption, and cost data into actionable insights for business and technology leaders.

The role blends data analytics, BI, dashboard development, AI operations and FinOps reporting to enable governance, optimization and capacity planning. Collaboration with cross-functional teams is essential.

Qualifications

Bachelor’s degree in data analytics, information systems, CS, statistics, BI or related field required.
2+ years of analytics, BI, reporting, data analysis or related function.
Experience developing Power BI dashboards and data visualizations for business or operational reporting.
Strong SQL skills for data extraction, transformation, analysis and reporting.
Experience translating findings into actionable business and operational insights.
Strong communication skills with ability to present findings to technical and business audiences.
Must be willing to work in the office three days a week.

Responsibilities

Develop and maintain Power BI dashboards and reporting measuring AI adoption, utilization, performance, cost, capacity and value.
Analyze AI operational data and KPIs, translating metrics into insights and recommendations.
Deliver executive and operational reporting to support AI governance, optimization, investments and planning.
Monitor AI consumption, cost, utilization, capacity and token usage across enterprise AI platforms.
Support AI forecasting, budgeting, FinOps reporting, and capacity planning.
Analyze adoption patterns, usage trends, and platform performance across AI technologies.
Develop trend analyses and forecasts to identify opportunities to improve adoption and value.
Gather, transform and analyze data from enterprise systems and AI platforms for reporting and decision-making.
Perform exploratory analysis to identify trends, anomalies, risks and opportunities for improvement.
Ensure data accuracy, consistency, completeness, and quality for dashboards and metrics.
Partner with business, technology, finance, governance and AI ops stakeholders to define reporting requirements.
Continuously improve reporting processes, methodologies, dashboard usability and visibility of AI outcomes.