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About the job

About This Role

Hearst Technology Services, Inc. (HTS) has an opportunity for a Cloud-focused Sr FinOps Data Analyst with experience analyzing costs and resource consumption of applications hosted on Amazon Web Services (AWS), Microsoft Azure, and Google (GCP) cloud IaaS and PaaS platforms. Hearst embraces modern, cloud-native approaches for our businesses. This position reports to the Senior FinOps Manager of Hearst’s Cloud Center of Excellence.

The Sr FinOps Data Analyst will be responsible for providing monthly cost analysis and optimization opportunities for a collection of approximately 50 subsidiary business units. The Sr FinOps Data Analyst will assist in maintaining the supporting cloud billing data as well as the front-end cost management toolset. They will analyze a portfolio of Hearst-owned businesses’ cloud consumption data and present insights to these internal customer businesses on a monthly basis.

We are looking for candidates who are highly analytical and detail-oriented, with strong communication skills. Public cloud platform domain knowledge is a must. Critical thinking and problem-solving skills are essential, along with a passion for research and discovery. Experience with high-trust, self-organizing, multi-disciplinary teams and the workflows that support them is important.

What You’ll Do

Monitor, analyze, and report on cloud spend 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 (e.g., CloudHealth, Cloudability, Apptio) to track spend trends, budget variance, and forecast accuracy

Identify cost optimization opportunities such as rightsizing, reserved instance/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 spend spikes, root-causing drivers and recommending corrective action

Maintain and improve cost allocation logic, including tagging compliance and unallocated spend reduction

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 spend, and third-party LLM API usage (e.g., OpenAI, Anthropic, Azure OpenAI)

Build visibility into AI cost drivers such as token consumption, request volume, model selection, and compute reservation vs. on-demand usage

Partner with data science and engineering teams to right-size GPU instances, evaluate reserved vs. 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 spend

What You’ll Bring

Required Qualifications

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/optimization tools such as **CloudHealth (VMware Aria Cost)**, Cloudability, or native cloud billing tools (AWS Cost Explorer, Azure Cost Management, 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 (SQL-based BI tools, Excel, Tableau, Power BI, or Looker)

Strong analytical and problem-solving skills with high attention to detail

Excellent communication skills, with the ability to translate technical cost data into business-relevant insights

Familiarity with cloud tagging strategies and cost allocation frameworks

Working knowledge of AI/ML cost drivers, including GPU/compute pricing, LLM API billing models (token- or request-based pricing), and cost differences across model providers and tiers

Preferred Qualifications

Microsoft Excel with advanced skills working with Pivot Tables and complex formulas

Knowledge of FinOps principles (FinOps Foundation certification 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 PowerBI or Tableau

Strong statistics and algebra math 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, Go

Educational Requirements

BS/BA degree in Computer Science, Engineering, Mathematics or relevant industry experience

Cloud Certifications, optional

FinOps Certified Practitioner (FOCP) certification, or willingness to obtain

Benefits

Hearst provides a competitive benefits package, including medical, dental, vision, disability and life insurance, 401(k), paid holidays and paid time off, employee assistance programs, and more.

Compensation

The base salary range below is the Company's good-faith estimate for this position in the posted work location at the time of posting. Final starting salary will be based on permissible, non-discriminatory factors, including but not limited to skills, experience, training, certifications, education, location and market considerations.

Base Salary Range: $102,500 — $125,000 USD