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).

In partnership with AVEVA and technology partners, System.AI designs, deploys, and evolves analytics across cloud, edge, and industrial environments to increase asset reliability, service efficiency and operational excellence.

As Analytics Technical Portfolio Manager, you own the end-to-end analytics lifecycle for the System.AI portfolio and ensure strong alignment with Service LOB (Eco Care DC, Cooling, and future segment offers).

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

The compensation range for this full-time position applies to candidates located within the United States.

Our salary ranges are determined by reviewing roles of similar responsibility and level.

Within the salary range, individual pay is determined by several factors including performance, knowledge, job related skills, experience, and relevant education or training.

Schneider Electric also offers a comprehensive benefits package to support our employees, inclusive of medical (with member reward points), 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.

You must submit an online application to be considered for the position.

The Company will accept applications on an ongoing basis until the position is filled.

Key Responsibilities End to End CBM Outcome & Analytics Lifecycle Ownership Own the full Analytics Lifecycle across all System.AI segments: Ideation → Incubation → Validation → Transfer to Industrialization → Bespoke Lifecycle Management 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) Coordinate with People.AI and platform teams to prepare next-generation deployment frameworks Solution Tooling & Process Ownership Design, manage and maintain System.AI tooling used to track, validate and govern analytics assets Ensure lifecycle traceability, versioning and controlled evolution across cloud, edge and OT environments Support SME’s and the Analytics Impact Leader in outcome definition, documentation and change-management processes Client 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 Required Skills &

Experience: 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 Understanding of OT networks and OT cybersecurity principles Industrial & Analytics Expertise:

Experience: creating and managing 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 Competencies: Strong analytical thinking and problem solving skills Ability to work across IT/OT boundaries 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 Let us learn about you!

Apply today.

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This position will be posted until filled.

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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).

In partnership with AVEVA and technology partners, System.AI designs, deploys, and evolves analytics across cloud, edge, and industrial environments to increase asset reliability, service efficiency and operational excellence.

As Analytics Technical Portfolio Manager, you own the end-to-end analytics lifecycle for the System.AI portfolio and ensure strong alignment with Service LOB (Eco Care DC, Cooling, and future segment offers).

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

The compensation range for this full-time position applies to candidates located within the United States.

Our salary ranges are determined by reviewing roles of similar responsibility and level.

Within the salary range, individual pay is determined by several factors including performance, knowledge, job related skills, experience, and relevant education or training.

Schneider Electric also offers a comprehensive benefits package to support our employees, inclusive of medical (with member reward points), 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.

You must submit an online application to be considered for the position.

The Company will accept applications on an ongoing basis until the position is filled.

Key Responsibilities End to End CBM Outcome & Analytics Lifecycle Ownership Own the full Analytics Lifecycle across all System.AI segments: Ideation → Incubation → Validation → Transfer to Industrialization → Bespoke Lifecycle Management 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) Coordinate with People.AI and platform teams to prepare next-generation deployment frameworks Solution Tooling & Process Ownership Design, manage and maintain System.AI tooling used to track, validate and govern analytics assets Ensure lifecycle traceability, versioning and controlled evolution across cloud, edge and OT environments Support SME’s and the Analytics Impact Leader in outcome definition, documentation and change-management processes Client 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

Required Skills &:

Experience: 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 Understanding of OT networks and OT cybersecurity principles Industrial & Analytics Expertise:

Experience: creating and managing 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 Competencies: Strong analytical thinking and problem solving skills Ability to work across IT/OT boundaries 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 Let us learn about you!

Apply today.