Vice President - Data & AI

Description

Summary:

This role will lead M3’s end‑to‑end data and AI strategy and execution – building the foundation that powers customer‑facing capabilities of our SaaS offerings, as well as the internal analytics, forecasting, and automation that drive operational efficiency, excellence, and insights. Reporting to the CTO, this role will oversee all aspects of data platform architecture, AI capabilities, and product enablement, governance, and analytics strategy.

The role requires a hands‑on technical leader who can balance innovation with predictability, ensuring that both internal teams and external customers derive measurable value from data and AI. This role is highly visible across the company, and you will collaborate with many different business and technical stakeholders to identify opportunities and solutions. It demands ownership and accountability and the ability to excite and motivate highly technical people.

• Deliver innovative data and AI capabilities that enhance M3’s products and customer experience
• Lead the design and development of AI‑enabled product capabilities, incl. task automation, predictive forecasting, variance analysis, fraud detection, etc. based on industry‑leading generative AI platforms
• Develop and implement sophisticated prompt engineering techniques to optimize AI language model performance and interaction strategies
• Build advanced predictive machine learning models using complex statistical techniques and algorithmic solutions for comprehensive data interpretation
• Create compelling data visualizations and narratives that transform technical insights into accessible strategic stories for stakeholder understanding
• Partner with Product and UX to define directly embedded data and AI experiences in customer‑facing products that improve user productivity and decision confidence
• Deliver mature internal data capabilities that empower cross‑functional internal teams – Finance, Sales, Marketing, Operations, Support, Executives – to make faster, data‑driven decisions around forecasting, sales pipeline, churn prediction, etc.
• Partner with business stakeholders on evaluating AI‑powered 3rd party tools and platforms to increase productivity
• Deliver a unified data platform from ingestion to formal models integrating CRM, ERP, billing, support, and product usage telemetry
• Establish and manage a comprehensive Data and AI framework that establishes ethical guidelines, responsible AI system design, and robust risk management protocols
• Deliver self‑service data models and dashboards to be used by analysis across the company
• Oversee the day‑to‑day technical, architectural, and process standards for data and AI engineering, providing guidance to managers and engineers at all levels
• Define and maintain a data and AI technology platform roadmap to manage platform upgrades, technical debt, and security risks
• Guide Dev Ops activities for production/operations in collaboration with IT Infrastructure teams
• Manage and optimize the resource model (local, hybrid, remote, offshore) with a balance of productivity, flexibility, and cost
• Act as a visionary and thought partner along with CTO and other technology and product leaders when it comes to platforms, frameworks and tools
• Measure and report on the productivity and quality of teams and progress of initiatives on the roadmap
• Lead, mentor, and manage individual technical contributors and managers/leads

• Minimum of 15 years of experience in data architecture and engineering, including at least 10 years of leading teams at the director/VP level
• Minimum of 3‑5 years of experience developing and deploying AI/ML solutions in a commercial SaaS setting
• Extensive experience managing data, AI, and engineering teams with manager‑level and individual contributor direct reports
• Experience creating sophisticated prompt engineering strategies across diverse Large Language Models (LLMs)
• Proficiency in AI, machine learning, statistical modeling, and predictive analytics solutions
  • Extensive technical experience with several of the following:
    • Public cloud platforms – MS Azure (preferred), AWS, GCP
    • Data platforms such as…