Data Analyst – AI Model Cost Analytics

About the Role

We are looking for a Data Analyst to build and operate the dashboards that track AI model costs

and consumption across the organization. You will turn large volumes of usage data into clear,

decision-ready insight that keeps AI spend aligned with forecast.

This is a high-visibility role: your dashboards and analyses will be used directly by leadership to

steer AI investment decisions.

Key Responsibilities

• Process and analyze large volumes of AI cost and usage data across teams and platforms.

• Track actual spend against forecast, surface variances early, and report detailed actuals.

• Design, build, and maintain leadership dashboards for AI model cost visibility.

• Identify and support cost-optimization opportunities with data-backed recommendations.

• Standardize metrics and definitions so cost reporting is consistent and trusted.

• Partner with engineering and finance stakeholders to refine reporting requirements.

Tech Stack

• Amazon Quick Suite for BI and dashboarding

• SQL for large-scale data analysis

• Dev360/program dashboard frameworks

• Data visualization and executive reporting

Required Skills & Experience

• 5–10 years of relevant professional experience in data analysis, BI, or analytics engineering.

• Proven, verifiable results delivering analytics and dashboard solutions that drove real business

decisions — with concrete examples of measurable impact.

• Hands-on experience with Amazon Quick Suite or comparable BI tooling.

• Strong SQL skills and comfort working with large, messy datasets.

• Experience building and maintaining program or executive dashboards.

• Strong attention to detail and ability to explain variances crisply.

• Experience building and/or leveraging AI agents (e.g., agentic workflows, LLM-based

automation, AI-assisted engineering tools) to improve productivity and outcomes.

Preferred Qualifications

• Prior domain experience in cloud FinOps.

• Familiarity with AI/LLM cost models (tokens, inference, training).

What We Look For

• Strong sense of ownership — takes end-to-end responsibility for outcomes, not just tasks.

• Self-motivated and proactive; able to operate independently with minimal supervision.

• A good team player who collaborates effectively across teams, geographies, and time zones.

• Proven track record of delivering measurable results in previous roles.