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Hearst

Global media and information services conglomerate

Senior FinOps Data Analyst

Data AnalysisPosted on Nov 11
Full-time$102.5k - $125kIn-person

About the Job

Requirements

  • At least 6 years of experience in FinOps, cloud cost management, financial analysis, or a related analytical role.
  • Proficiency in SQL for querying, transforming, and analyzing large datasets.
  • Hands-on experience with cloud cost management and optimization tools such as CloudHealth (VMware Aria Cost), Cloudability, or native cloud billing tools, including AWS Cost Explorer, Azure Cost Management, or GCP Billing.
  • Solid understanding of cloud provider billing models, including reserved instances, savings plans, spot pricing, and committed use discounts.
  • Experience building Business Intelligence reports and dashboards using SQL-based BI tools, Excel, Tableau, Power BI, or Looker.
  • Strong analytical and problem-solving skills with high attention to detail.
  • Ability to translate technical cost data into business-relevant insights through excellent communication skills.
  • Familiarity with cloud tagging strategies and cost allocation frameworks.
  • Working knowledge of AI/ML cost drivers, including GPU/compute pricing, LLM API billing models such as token- or request-based pricing, and cost differences across model providers and tiers.
  • A BS/BA degree in Computer Science, Engineering, or Mathematics, or relevant industry experience.
  • FinOps Certified Practitioner certification or willingness to obtain it.

Responsibilities

  • Monitor, analyze, and report on cloud spending across Amazon Web Services, Azure, and Google Cloud environments.
  • Lead monthly cloud consumption and cost optimization business review meetings with Hearst-owned businesses.
  • Build and maintain dashboards and reports using SQL and cost management platforms such as CloudHealth, Cloudability, and Apptio to track spending trends, budget variance, and forecast accuracy.
  • Identify cost optimization opportunities, including rightsizing, reserved instance and savings plan coverage, idle resource elimination, and storage tiering.
  • Partner with engineering teams to implement tagging strategies, cost allocation models, and showback/chargeback frameworks.
  • Support monthly and quarterly cloud spend reviews with business units and leadership.
  • Investigate cost anomalies and spending spikes, identify root causes, and recommend corrective action.
  • Maintain and improve cost allocation logic, including tagging compliance and reduction of unallocated spend.
  • Collaborate with Finance on budgeting, forecasting, and variance analysis for cloud costs.
  • Assist in developing and refining FinOps policies, KPIs, and maturity roadmaps.
  • Stay current on cloud provider pricing models, discount programs, and new cost management tooling.
  • Track and analyze costs associated with AI/ML workloads, including GPU/accelerator utilization, model training and inference spending, and third-party LLM API usage such as OpenAI, Anthropic, and Azure OpenAI.
  • Build visibility into AI cost drivers such as token consumption, request volume, model selection, and compute reservation versus on-demand usage.
  • Partner with data science and engineering teams to right-size GPU instances, evaluate reserved versus spot capacity for training jobs, and identify underutilized AI infrastructure.
  • Support forecasting and budgeting for AI initiatives, accounting for the variable and rapidly scaling nature of AI/ML spending.

Desired Qualifications

  • Advanced Microsoft Excel skills, including Pivot Tables and complex formulas.
  • Knowledge of FinOps principles; FinOps Foundation certification is a plus.
  • Experience monitoring AI/LLM usage and cost through platforms such as Anthropic Console, OpenAI usage dashboards, Azure AI cost management, or third-party AI cost tools.
  • Experience with business intelligence tools such as Power BI or Tableau.
  • Strong statistics and algebra skills.
  • Prior experience working directly with engineering teams on cost-aware architecture decisions.
  • Ability to read or write scripts in one or more modern scripting or programming languages: R, SQL, Python, Scala, Java, C++, Ruby, PowerShell, or Go.
  • Optional cloud certifications.

About the Company

Hearst

Global media and information services conglomerate

Hearst is a global, diversified media, information, and services group with magazines, newspapers, TV and radio stations, and business information brands. It earns revenue from advertising, subscriptions, and the sale of information services across its media brands, including Fitch Ratings. Its products span consumer magazines (Cosmopolitan, ELLE, Esquire, Men's Health), TV and radio broadcasting, and data services for automotive, medical, and financial industries. Its goal is to be a leading worldwide provider of trusted media content and data-driven information services for individuals and large businesses.

Company size
5,001-10,000
Company stage
Not listed
Total funding
Not listed
Headquarters
New York City, New York
Founded
1887

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