Sr IT Financial Analyst - Cloud

RadNet•UNAVAILABLE, OH

20h

About The Position

Artificial Intelligence; Advanced Technology; The very best in patient care. With decades of expertise, RadNet is Leading Radiology Forward. With dynamic cross-training and advancement opportunities in a team-focused environment, the core of RadNet’s success is its people with the commitment to a better healthcare experience. When you join RadNet as a Senior IT Financial Analyst - Cloud, you will be joining a dedicated team of professionals who deliver quality, value, and access in the 21st century and align all stakeholders- patients, providers, payors, and regulators to achieve the best clinical outcomes.

Requirements

Bachelor's degree in Finance, Accounting, Information Systems, Business Analytics, or a related field; equivalent relevant experience will be considered.
4 to 7 years of experience in IT financial analysis, FinOps, technology business management, cloud cost management, or a closely related discipline.
Demonstrated experience developing financial models, total cost of ownership comparisons, driver-based forecasts, unit economics, and budget variance analysis.
Hands-on experience analyzing cloud billing and consumption data, preferably in Google Cloud, including billing exports, pricing, discount structures, and committed-spend concepts.
Advanced Excel or equivalent financial-modeling skills and SQL proficiency for querying billing, usage, and operational data.
Experience combining technology cost data with business or operational metrics to support planning and investment decisions.
Strong written and verbal communication skills, including the ability to translate technical usage and architecture into clear financial narratives for Finance and leadership.
Ability to work across technical, financial, product, and operational teams in a shared-accountability environment.
Experience in healthcare IT, medical imaging, or health technology SaaS environments.
Familiarity with RIS/PACS, DICOM workflows, imaging study volume, or medical imaging storage and retention requirements.
Experience comparing on-premises and cloud infrastructure economics or supporting infrastructure migration and workload-placement decisions.
Experience with SaaS or multi-tenant product cost modeling, cost to serve, gross-margin analysis, or customer and product unit economics.
Experience with CloudZero, Google Cloud Billing, BigQuery, Looker or Looker Studio, Google Cloud Recommender or Active Assist, or comparable FinOps and analytics platforms.
FinOps Certified Practitioner or comparable FinOps Foundation certification.
Familiarity with healthcare security, privacy, audit, or data-retention considerations.
Analytical rigor and disciplined management of assumptions, baselines, and data quality.
Ability to connect technology consumption and cost to measurable business outcomes and operational demand.
Financial storytelling that makes complex technical economics understandable and actionable.
Strong partnership across Finance, cloud, platform, infrastructure, data, engineering, product, and leadership teams.
Balanced judgment that considers cost alongside performance, resiliency, security, compliance, clinical availability, and business growth.
Comfort working across RadNet and DeepHealth in a shared operating model with multiple stakeholders and accountability boundaries.

Responsibilities

Develop financial models that connect technology costs to relevant business and operational metrics, creating decision-quality unit economics for infrastructure, cloud platforms, data platforms, and technology-enabled products and services.
Partner with business, operations, Finance, product, and technology teams to identify appropriate cost drivers for each workload, including imaging study volume, modality mix, site count, customer count, product usage, transaction volume, storage growth, compute consumption, and data retention.
Develop and maintain metrics such as cost per imaging study, cost per site, cost per customer, cost per transaction, cost per terabyte, and other workload-specific measures.
Analyze whether technology costs are scaling proportionally with business growth and identify changes in cost efficiency, operating leverage, gross margin, or cost to serve over time.
Normalize costs against business volume so alternatives can be compared consistently using both absolute spend and unit economics.
Develop total cost of ownership and scenario models comparing on-premises infrastructure, colocation or hosted infrastructure, public cloud, SaaS, and hybrid deployment models.
Model hardware acquisition and refresh cycles, maintenance and support, software licensing, datacenter and networking costs, cloud consumption, storage growth, contractual commitments, migration costs, and relevant operational support requirements.
Partner with architecture, infrastructure, cloud, and platform teams to quantify the short-term and long-term financial tradeoffs of workload placement, modernization, migration, consolidation, and platform replacement decisions.
Maintain reusable three- to five-year models that allow leadership to evaluate multiple growth, capacity, architecture, and investment scenarios.
Track one-time transition or migration costs separately from ongoing run-rate costs and validate realized outcomes against approved business cases.
Develop driver-based monthly, quarterly, and annual forecasts that connect technology spend to imaging volume, customer and product growth, site onboarding, storage and data growth, utilization, architecture changes, and other measurable business drivers.
Prepare budget-to-actual and forecast variance analysis, identify the business and technical causes of material changes, and communicate financial implications and recommended follow-up actions.
Support annual capital and operating budget cycles, multi-year infrastructure planning, accruals, cloud invoice reconciliation, committed-spend tracking, and financial reporting.
Create concise reporting for Finance and leadership covering run rate, forecast, variance, unit economics, cost drivers, savings opportunities, savings realization, risks, and decisions required.
Build scenario models for acquisitions, new market or site expansion, imaging volume growth, customer adoption, product scaling, increased resiliency, retention changes, and infrastructure modernization.
Work with IT Financial Ops Manager and Director to integrate Cloud reporting into other financial reporting and analytics related to software spend.
Partner with the existing RadNet Cloud Operations, Platform Engineering, and FinOps resources and the DeepHealth FinOps practice to mature a shared FinOps operating model.
Participate in and help operationalize a recurring cross-functional FinOps committee across RadNet IT, DeepHealth, and Finance, including standardized reporting, decision tracking, ownership, and follow-up.
Use and mature existing capabilities including CloudZero, Google Cloud Billing and billing exports, BigQuery financial datasets, Looker and Looker Studio cost and anomaly dashboards, and native Google Cloud cost-management tools.
Partner with technical teams to improve and govern cost baselines, allocation methodologies, resource labels and tags, application ownership, environment classification, product or customer attribution, anomaly detection, and financial accountability.
Support ongoing work with the Google Cloud FinOps practice and help translate recommendations into prioritized financial opportunities, measurable outcomes, and sustainable operating processes.
Develop FinOps KPIs and maturity measures that show allocation coverage, forecast accuracy, anomaly response, optimization progress, commitment utilization, and realized financial outcomes.
Monitor, analyze, and report on Google Cloud consumption and spend across compute, Kubernetes, storage, networking, managed databases, BigQuery, and other material services.
Identify, quantify, and prioritize optimization opportunities involving commitments, rightsizing, storage lifecycle and tiering, idle resource reclamation, architecture choices, and consumption patterns.
Work with engineering and FinOps teams to validate optimization opportunities against performance, availability, resiliency, security, compliance, and operational requirements.
Measure and report realized savings and cost avoidance using agreed financial baselines, while technical teams retain accountability for implementation decisions and infrastructure changes.
Maintain showback and, where appropriate, chargeback models across business units, environments, applications, products, imaging sites, and customer accounts.
Model the cost and capacity implications of enterprise data and analytics platforms, including BigQuery storage, query and compute consumption, data pipelines, and related services.
Develop cost-to-serve and unit-economic analysis for internal platforms and customer-facing healthcare technology products, including appropriate fixed and variable cost treatment.
Partner with product, data, infrastructure, and engineering teams to forecast how platform costs change with adoption, customer growth, study volume, storage and retention, feature usage, and service-level requirements.
Support product, pricing, investment, and margin discussions with transparent assumptions and repeatable financial models.
Analyze Google Cloud agreement terms, committed-spend structures, discounts, consumption risk, and financial performance; support renewal, commitment, and negotiation cycles.
Support business cases and due diligence for acquisitions, new markets, site expansion, platform migrations, infrastructure refreshes, SaaS adoption, and other technology investments.
Reconcile vendor, billing, and technical consumption data and partner with Finance to establish consistent definitions for cloud spend, infrastructure run rate, committed spend, forecast variance, and savings realization.
Serve as a financial translation layer between technical FinOps teams and Finance, connecting consumption data, cloud billing, forecasts, budgets, accruals, and executive reporting.
Work closely with Cloud Operations, Platform Engineering, infrastructure, data engineering, product, Finance, procurement, and DeepHealth teams across shared priorities.
Translate technical architecture and consumption decisions into clear financial narratives, options, assumptions, and recommendations for non-technical stakeholders and leadership.
Support audit and compliance needs related to technology spend, data retention, allocation, and financial controls in a regulated healthcare environment.