Data Scientist/ Multi-cloud architecture

Finops Data ScientistWe are seeking a FinOps Data Scientist with strong multi-cloud architecture expertise to join our FinOps Multi-Cloud Cost Optimization program.This is a hybrid role combining the data science depth needed to deliver advanced cost analytics, forecasting, and automation, with the cloud architecture acumen required to design and guide cost-efficient, scalable, and compliant multi-cloud environments.The successful candidate will operate as both a hands-on practitioner and a thought leader, advising on cloud financial governance and architecture patterns while building predictive models and automation to maximize efficiency across Azure, AWS, and GCP.Key ResponsibilitiesDevelop and refine predictive models for multi-cloud cost forecasting, anomaly detection, and optimization scenario analysis.Apply machine learning techniques to detect inefficiencies, usage anomalies, and cost-saving opportunities.Translate complex cost and usage data into actionable insights for cloud service owners, finance, and architecture teams.Leverage and integrate data from Cloudability (Apptio), Azure Cost Management, AWS Cost Explorer, and GCP Billing into unified analytics workflows.Multi-Cloud Architecture EnablementProvide architectural guidance to design cost-efficient, secure, and scalable solutions across Azure, AWS, and GCP.Define and enforce tagging, labeling, and cost allocation frameworks to enable accurate chargeback/showback reporting.Collaborate with FinOps Architects to align optimization strategies with landing zones, VPC/VNet architectures, container platforms (AKS, EKS, GKE), and hybrid connectivity patterns.Recommend architectural adjustments to reduce spend (e.g., rightsizing compute, leveraging spot/preemptible instances, optimizing storage tiers).Optimization & AutomationPartner with automation engineers to build API-driven workflows for cost anomaly alerts, automated remediation, and scaling policies.Implement infrastructure-as-code templates (e.g., Terraform, Bicep) to standardize cost-conscious deployments.Conduct what-if analyses to evaluate the financial impact of proposed architectural or operational changes before implementation.Stakeholder Engagement & GovernanceServe as a trusted advisor to enterprise architects, finance, and cloud operations teams.Present recommendations to senior leadership, balancing technical feasibility, cost impact, and governance alignment.Ensure all FinOps activities align with client security, compliance, and cost governance frameworks.Required Qualifications5+ years in data science, cloud analytics, or applied machine learning, with at least 2 years in a FinOps or cloud architecture-focused role.Proficiency in Python (Pandas, NumPy, Scikit-learn) and SQL for large dataset analysis.Strong understanding of multi-cloud architecture principles and cost optimization strategies.Experience with Cloudability (Apptio), Azure Cost Management, AWS Cost Explorer, GCP Billing APIs.Knowledge of FinOps principles and enterprise cloud governance models.Ability to clearly communicate complex data and architecture trade-offs to varied audiences.Preferred QualificationsExperience with machine learning on cloud-native platforms (Azure Machine Learning, AWS SageMaker, GCP Vertex AI).Hands-on experience with infrastructure-as-code (Terraform, Bicep) and automation pipelines (GitHub Actions, Azure DevOps).Familiarity with container orchestration (AKS, EKS, GKE) and associated cost considerations.FinOps Certified Practitioner or Architect certification.Background in large enterprise multi-cloud transformations.Why Work With UsHybrid Expertise: Operate at the intersection of data science and cloud architecture to deliver measurable business impact.Impact at Scale: Optimize cloud costs for one of the world's largest enterprise IT environments.Thought Leadership: Influence both architecture and financial governance strategies in a high-visibility program.Global Collaboration: Work with a cross-functional FinOps team across US, India, and LATAM.