Senior Quantitative Model Solutions Specialist

• Lead or participate in moderately complex model maintenance and optimization initiatives related to operating processes, controls, reporting, testing, implementation, and documentation
• Review and analyze moderately complex data sets, quantitative models, and model outputs to validate model efficiency and results in support of business initiatives
• Advise and guide team on moderately complex model optimization and processes strategies
• Independently resolve moderately complex issues and lead team to meet project deliverables while leveraging solid understanding of policies and compliance requirements
• Collaborate and consult with peers, colleagues, and managers to resolve issues and achieve goals
• Responsible for the execution of enterprise AI/ML platform initiatives, supporting model lifecycle activities across hybrid environments
• Partner with business and technology teams to translate requirements into actionable delivery plans
• Facilitate governance forums, leadership reviews, and stakeholder engagements to provide transparency into program status, risks, and outcomes
• Develop and maintain standardized reporting, metrics, and dashboards to track platform adoption, operational performance, and business outcomes
• Support Platform administration operations, including data governance, approvals, and compliance with enterprise data and privacy standards
• Coordinate cross-functional teams to resolve blockers, manage escalations, and ensure timely delivery of AI/ML solutions
• Contribute to roadmap planning, release communications, and change management activities across enterprise AI/ML platforms
• Support large-scale transformation initiatives including platform migration, cost optimization tracking, and operational readiness across cloud and on-prem environments
• Organize and facilitate workshops, planning sessions, and stakeholder engagements to accelerate adoption of enterprise AI/ML capabilities
• Strong communication skills with the ability to engage senior stakeholders and translate complex technical concepts into business-aligned insights

4+ years of quantitative solutions engineering, model solutions or quantitative model operations experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education

• Bachelor’s degree or higher in a quantitative discipline such as mathematics, statistics, engineering, economics, computer science, or related field
• Proven ability in product management, solution management, program delivery, or technical product ownership, with a focus on Gen AI, AI/ML platforms, APIs, and/or cloud-native solutions
• 5+ Experience across the Gen AI AI/ML lifecycle, including data management, feature engineering, model development, deployment, monitoring/observability, and model governance and risk controls
• 5+ Experience with enterprise MLOps and/or LLMOps practices, including CI/CD pipelines, model lifecycle automation, and monitoring frameworks
• 3+ years of hands-on experience with public cloud technologies (Google Cloud Platform and/or Microsoft Azure) and container orchestration (Docker, Kubernetes, OpenShift)
• Familiarity with APIs, distributed systems, and cloud-native architectures supporting AI/ML workloads
• Working knowledge of enterprise platform components and services such as Vertex AI, BigQuery, OpenShift, IBM Cloud Pak for Data (CP4D), and large-scale distributed model execution platforms
• Strong analytical mindset with ability to track performance metrics, cost efficiency, and operational outcomes
• Proven ability to develop and execute executive-level roadmaps, dashboards, and reporting that clearly demonstrate business impact and risk posture