Data Analyst – AI Model Cost Analytics

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I have urgent requirements for Data Analyst – AI Model Cost Analytics. If you are interested, please share your resume.

Position: Data Analyst – AI Model Cost Analytics 

Location: San Diego, CA - Remote

Duration: 12+ Months and Contract

Job Description

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.