## About the Role

Point72 is seeking a FinOps professional to optimize financial operations across cloud, SaaS, artificial intelligence, and machine learning workloads. The role will improve cost visibility, support forecasting and budgeting, and help maximize the value of technology investments.

You will collaborate with Technology, Finance, Procurement, engineering teams, and business owners. The position will contribute to cost governance, vendor negotiations, financial planning, and the development of cost-conscious resource and license consumption practices.

## Key Responsibilities

– Partner with Technology, Finance, and Procurement teams to align technology cost strategies with business objectives.
– Educate engineering and business stakeholders on cloud financial management practices.
– Develop processes and tooling that improve cost visibility across cloud, SaaS, and AI workloads.
– Support budgeting cycles, commitment decisions, and vendor negotiations.
– Identify trends, anomalies, cost drivers, and optimization opportunities across technology spending.

## Required Skills

– At least 7 years of experience in financial management, cloud operations, or technology cost management.
– At least 3 years of hands-on FinOps experience.
– Bachelor’s degree in finance, computer science, information technology, or a related discipline.
– Strong understanding of AWS, Google Cloud, or Azure cost structures.
– Knowledge of cost models for AI and machine learning services, including GPU instances, managed AI platforms, and large language model API usage.
– Experience with financial analysis and modeling for forecasting, budgeting, commitment decisions, and vendor negotiations.
– Strong data analysis skills, including querying and manipulating large datasets and creating clear visualizations.
– Excellent analytical, problem-solving, communication, and interpersonal skills.
– Ability to work independently and collaboratively in a fast-paced environment.
– Commitment to the highest ethical standards.

## Cloud Platforms & Technologies

### Cloud Providers
– Amazon Web Services (AWS)
– Google Cloud
– Microsoft Azure

### Artificial Intelligence & Machine Learning
– Artificial intelligence workloads
– Machine learning workloads
– Managed AI platforms
– Large language model APIs
– GPU-intensive infrastructure

### SaaS & Data
– SaaS platforms and licensing
– Large dataset analysis
– Data visualization

## FinOps Responsibilities

– Optimize cloud financial operations across cloud, SaaS, AI, and machine learning workloads.
– Analyze cloud spend, SaaS licensing, model inference, and usage-based AI consumption.
– Monitor large language model API usage and GPU infrastructure for cost trends and anomalies.
– Implement tagging standards, tooling, and processes to improve cost visibility.
– Build financial models for expenditure forecasting, budgeting, commitment decisions, and vendor negotiations.
– Design cost allocation, showback, and chargeback models for teams, applications, and use cases.
– Identify and implement cost optimization opportunities.
– Promote cost-conscious consumption practices among engineering and business stakeholders.

## Benefits

– Fully paid healthcare benefits
– Parental and family leave
– Mental and physical wellness programs
– Volunteer opportunities
– Nonprofit matching gift program
– Support for employee-led affinity groups
– Tuition assistance
– 401(k) savings plan with employer match

## Compensation

– Annual base salary: **$170,000–$250,000 USD**
– Additional discretionary bonus compensation
– Comprehensive benefits package
– Final compensation may vary based on location, experience, education, and skills.

## Useful Links

– Company Website: https://point72.com/

## Why You Might Be Interested

This role offers the opportunity to shape FinOps practices across cloud, SaaS, and emerging AI workloads. You will work across Technology, Finance, Procurement, engineering, and business teams while contributing to forecasting, cost governance, and vendor strategy. The position also provides exposure to large language model consumption and GPU-intensive infrastructure within a global investment firm.