Senior AI FinOps Analyst: Cost Modeling & Optimization

RELX; Raleigh (NC); On-site; USD 105,000 - 175,000; Full time

Benefits offered by this job

Annual incentive bonus

Flexible working hours

Job summary

LexisNexis Legal & Professional, part of RELX, seeks a Senior FinOps Analyst in Raleigh, NC to own AI cost modeling and attribution across tokens, models, products, teams, and shared infrastructure. You will partner with engineering, product, and finance to improve visibility, forecasting, and cost efficiency.

You will build Python pipelines, automate reporting, and develop BI dashboards to communicate cost drivers to technical and finance audiences.

Qualifications

• Experience in FinOps, cloud cost mgmt, or analytics.

Responsibilities

• Own AI cost modeling and attribution across tokens, models, products, teams, and shared infrastructure.
• Define unit-cost metrics that distinguish usage growth from efficiency changes.
• Maintain accurate, explainable cost data with clear lineage and defensible methodology.
• Build Python pipelines that normalize telemetry, provider API data, platform usage, and cloud billing into trusted datasets.
• Automate recurring reporting, month-end close support, and anomaly detection.
• Develop practical BI dashboards for engineering teams and credible reporting for Finance stakeholders.
• Analyze cost movements and explain drivers, expected impacts, and forward-looking implications.
• Identify, quantify, and track optimization opportunities across model selection, prompt efficiency, caching, batching, retrieval, commitments, and tooling overlap.

Skills

FinOps

Cloud cost mgmt

Data analytics

Python

SQL

Dashboarding

Tools

Power BI

Tableau

Job description

LexisNexis Legal & Professional, part of RELX, seeks a Senior FinOps Analyst in Raleigh, NC to own AI cost modeling and attribution across tokens, models, products, teams, and shared infrastructure. You will partner with engineering, product, and finance to improve visibility, forecasting, and cost efficiency.

You will build Python pipelines, automate reporting, and develop BI dashboards to communicate cost drivers to technical and finance audiences.