Job Description Summary

The Analytics Foundry Leader is a technical visionary and organizational architect for the Heavy-Duty fleet’s data intelligence engine. This role leads a high-performing organization of 20+ specialized data scientists, machine learning engineers, and digital architects responsible for transforming massive, complex global fleet datasets into high-fidelity predictive analytics.
The defining opportunity of this role is to scale a "factory of insights" that powers the entire HDSE organization and improves the balance of preventative versus responsive support to our customers.

This leader will drive a collaborative model where the Foundry Team partners directly with the Applied Reliability and Product Service Teams to define the "what" (identifying top sources of unreliability and critical failure modes) and with M&D Insights Central to define the "how" (operationalizing the diagnostics and the delivery of those insights). By standardizing the development, validation, and deployment of advanced AI/ML models, this leader enables the Fleet Operational Intelligence organization to deliver proactive reliability at a global scale. This leader will also deliver Fleet Analytics to support key activities including NPIs and RCAs.

This is a critical leadership role that bridges the gap between raw engineering data and commercial value, requiring deep technical expertise, a relentless focus on model quality, and the ability to build and retain world-class data talent.

Job Description

Roles & Responsibilities:

• Scale the Innovation Factory: Direct a team of 20+ data scientists and engineers to build, test, and deploy a robust pipeline of predictive and diagnostic models. Own the end-to-end lifecycle of digital products, from prototype to production at scale.
• The "What vs. How" Partnership: Establish and maintain deep collaborative interfaces:
  • Partner with Applied Reliability Engineering and Product Service Engineering to define the "what"—prioritizing analytics efforts against the most critical fleet reliability drivers and top failure modes.
  • Partner with M&D Insights Central to define the "how"—ensuring technical scripts and digital insights are operationalized effectively for regional execution.
• Technical Strategy & Architecture: Define the technical roadmap for the Analytics Foundry, ensuring that AI/ML capabilities, data pipelines, and diagnostic scripts are unified, maintainable, and aligned with the "Reliability → Analytics → Diagnostics → Closure" operating model.
• Talent Leadership: Build, mentor, and retain a world-class team of data scientist professionals. Cultivate a culture of technical rigor, curiosity, and rapid experimentation while ensuring high output and quality standards.
• Model Integrity & Governance: Govern the quality, health, and efficacy of all deployed models. Minimize false positives and maximize "signal-to-noise" ratios, ensuring the Fleet Operational Intelligence team and Regional Poles trust and utilize analytics-driven insights as a primary input for engineering decisions.
• Tooling & Standardization: Drive the consolidation and modernization of diagnostic tools. Eliminate "tool sprawl" and ensure all analytics workflows adhere to global cybersecurity, data integrity, and engineering standards.
• Commercial & Customer Impact: Translate complex technical output into actionable business intelligence. Work with the broader intelligence team to ensure that digital products are directly contributing to reduced unplanned downtime and increased service value for 600+ global customers.
• Continuous Improvement: Champion Lean methodologies within the digital workflow, focusing on cycle-time reduction for model development and deployment.

Required Qualifications

• Bachelor’s degree in Computer Science, Data Science, Engineering, Applied Mathematics, Physics, or related technical field from an accredited university.
• Minimum 10 years of progressive technical leadership across multiple engineering or technology disciplines.
• Minimum 5 years of demonstrated experience leading high-performing, multi-disciplinary technical teams of 20+ professionals.
• Demonstrated track record of taking AI/ML models from R&D/prototype environments to enterprise-scale deployment within a complex industrial or services environment.

Desired Characteristics

• Advanced degree (MS/PhD) in a quantitative discipline (e.g., Data Science, AI/ML, Operations Research).
• Deep expertise in industrial IoT, predictive maintenance, or power generation services.
• A "Product Mindset" applied to analytics—understanding that models are products that must serve a user and deliver a business outcome.
• Exceptional ability to translate abstract technical challenges into clear strategic priorities for non-technical leadership.
• Demonstrated ability to influence cross-functional peers (e.g., Engineering, IT, Product Service) to adopt new digital workflows.
• Lean practitioner who applies rigorous process discipline to creative and technical work.
• Servant leadership style: focused on removing blockers for a highly specialized team while ensuring alignment with the broader business vision.
• Data-driven decision-maker who acts decisively despite ambiguity.
• One Team mentality—leads horizontally, breaks down organizational silos, and keeps the customer outcome at the center of every decision.

Note

Note:
To comply with US immigration and other legal requirements, it is necessary to specify the minimum number of years' experience required for any role based within the USA. For roles outside of the USA, to ensure compliance with applicable legislation, the JDs should focus on the substantive level of experience required for the role and a minimum number of years should NOT be used.

This Job Description is intended to provide a high level guide to the role. However, it is not intended to amend or otherwise restrict/expand the duties required from each individual employee as set out in their respective employment contract and/or as otherwise agreed between an employee and their manager.

Additional Information

 

 

For candidates applying to a U.S. based position, the pay range for this position is between $155,300.00 and $258,800.00. The Company pays a geographic differential of 110%, 120% or 130% of salary in certain areas. The specific pay offered may be influenced by a variety of factors, including the candidate’s experience, education, and skill set.

 

 

Bonus eligibility: discretionary annual bonus.

 

 

This posting is expected to remain open for at least seven days after it was posted on September 03, 2026.

 

 

Available benefits include medical, dental, vision, and prescription drug coverage; access to Health Coach from GE Vernova, a 24/7 nurse-based resource; and access to the Employee Assistance Program, providing 24/7 confidential assessment, counseling and referral services. Retirement benefits include the GE Vernova Retirement Savings Plan, a tax-advantaged 401(k) savings opportunity with company matching contributions and company retirement contributions, as well as access to Fidelity resources and financial planning consultants. Other benefits include tuition assistance, adoption assistance, paid parental leave, disability benefits, life insurance, 12 paid holidays, and permissive time off.

 

 

GE Vernova Inc. or its affiliates (collectively or individually, “GE Vernova”) sponsor certain employee benefit plans or programs GE Vernova reserves the right to terminate, amend, suspend, replace, or modify its benefit plans and programs at any time and for any reason, in its sole discretion. No individual has a vested right to any benefit under a GE Vernova welfare benefit plan or program. This document does not create a contract of employment with any individual.