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# FinOps Specialist

- **Company:** POINT72, L.P.
- **Location:** New York, NY, United States
- **Experience:** Experienced
- **Salary:** $170,000.0 - $250,000.0
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Data Analysis, Microsoft Azure, Big Data, Software as a Service, Cloud Computing, Machine Learning, Google Cloud, AI Platforms, Information Technology
- **Published:** September 23, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=9c4e9bf89c7d3dc6

## About the Role

* 7+ years of relevant experience in financial management, cloud operations, or technology cost management, including at least three years of hands-on FinOps experience
 * Bachelor's degree in finance, computer science, information technology, or a related field
 * Strong understanding of cloud platforms, such as AWS, Google Cloud, or Azure, and their cost structures
 * Familiarity with cost structures for artificial intelligence and machine learning services, including GPU instances, managed AI platforms, and large language model API usage
 * Proficiency in financial analysis and modeling for forecasting, budgeting, commitment decisions, and vendor negotiations
 * Strong data analysis skills, including querying and manipulating large datasets and building clear visualizations for stakeholder decision-making
 * Excellent analytical and problem-solving skills for identifying cost drivers, trends, and optimization opportunities
 * Strong communication and interpersonal skills, with the ability to work independently and collaboratively in a fast-paced environment
 * Commitment to the highest ethical standards

## Description

* Optimize cloud financial operations to maximize value from cloud investments, including rapidly growing artificial intelligence (AI) and machine learning workloads
 * Provide actionable insights on cloud spend, SaaS license optimization, and emerging AI cost drivers, including model inference and usage-based consumption
 * Implement tooling, tagging standards, and processes that improve cost visibility and optimization across cloud, SaaS, and AI workloads
 * Monitor large language model API consumption and GPU-intensive infrastructure to identify cost trends, anomalies, and optimization opportunities
 * Build financial models to forecast cloud, SaaS, and AI expenditures for budgeting cycles, commitment decisions, and vendor negotiations
 * Design cost allocation, tagging, showback, and chargeback models that attribute spend to the teams, applications, and use cases driving it
 * Educate engineering and business owners on cloud financial management practices that build cost-conscious habits around resource and license consumption
 * Partner across the firm's technology, finance, and procurement teams to align cloud and technology cost strategies with business objectives and firmwide planning


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