Head of Analytics Portfolio Manager

About the role

System.AI is a Schneider Electric global CTO/ETO Center of Excellence delivering predictive insights and Condition-Based Maintenance (CBM) outcomes for complex power and cooling systems. Today, System.AI primarily supports Data Center environments, with planned expansion into additional market segments requiring advanced analytics and industrialized CBM capabilities (industrial facilities, healthcare, energy distribution, microgrids and other mission-critical infrastructures).

Responsibilities

• End to End CBM Outcome & Analytics Lifecycle Ownership
• Maintain long-term ownership of customer-specific analytics not intended for standardization
• Translate Service LOB requirements into validated, measurable CBM outcomes that reduce interventions, improve uptime and mitigate risk
• Define performance criteria and monitor analytics performance across deployments and customer segments
• Support next-generation analytics deployment (agentic models, LLM-enabled CBM workflows, edge intelligence)
• Career Engagement & Delivery
• Engage with customers across segments to define, validate and refine CBM analytic outcomes
• Lead tuning and validation cycles during pilot phases and deployment stages
• Capture segment specific operational insights and feed them back into System.AI and LOB roadmaps
• Operational Insights Support
• Recruitment and coordination of internal and contract technical resources
• Strengthen integration with Schneider Electric platforms (EBO, PME, PSO, DCIM, EAA and future segment-specific platforms)
• Contribute to the evolution of Schneider Electric’s edge, IoT and analytics standards for cross-segment scalability

Requirements

• Information Technology: Strong Experience With Windows And Cloud Environments (Azure Preferred)
• Knowledge of Cloud DevOps practices, cloud optimization and cost-optimization strategies
• Understanding of cybersecurity practices including network traffic whitelisting and secure configuration
• Operational Technology: Experience with industrial communication protocols such as OPC and Modbus
• Experience with industrial asset models
• Hands-on experience with predictive analytics, industrial data engineering and analytic toolsets
• Familiarity with industrial and data center environments preferred
• Experience in industrial services or field-service operations is an advantage
• Technical Tools & Platforms: Python, C#, Postman Azure services (Azure ML experience is an advantage)
• API integration and cloud-based data interchange
• Analytics and monitoring tools related to UPS, cooling, switchgear, batteries and other critical systems

Qualifications

• Strong analytical thinking and problem solving skills
• Excellent communication skills with customers and internal teams
• Ability to lead deployments and manage multiple global initiatives
• Comfortable with travel and client-facing interactions
• Motivates and aligns SME’s, Service LOB, engineering partners and external stakeholders
• Builds a collaborative, inclusive working environment across global teams and segments
• Encourages open communication, shared ownership and cross-functional problem solving
• Recognizes contributions, fosters trust and drives collective engagement toward shared outcomes

Skills

• Python
• C#
• Postman
• Azure services (Azure ML experience is an advantage)

Benefits

• Comprehensive benefits package including medical, dental, vision, and basic life insurance, Benefit Bucks (credits to apply towards your benefits), flexible work arrangements, paid family leaves, 401(k) + match, well-being and recognition (including service anniversary) programs, 12 holidays per year, 15 days of paid time off per year (pro-rated in the first year of employment based on start date), opportunity to purchase company stock (eligibility depends on start date), and military leave benefits.

Pay

The expected compensation range for this U.S. based position is $162,000 - $185,000 per year, which includes base pay and short-term incentive.

Schedule

The position is full-time.