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GE Vernova

Builds equipment and software for electric power

Analytics Foundry Leader

Engineering LeadershipConfirmed live in the last 24 hours
Full-timeIn-person

About the Job

Requirements

  • A bachelor's degree in Computer Science, Data Science, Engineering, Applied Mathematics, Physics, or a related technical field from an accredited university is required.
  • A minimum of 10 years of progressive technical leadership across multiple engineering or technology disciplines is required.
  • A minimum of 5 years leading high-performing, multidisciplinary technical teams, including leaders of other people, is required.
  • A demonstrated track record of taking AI/ML models from research and development or prototype environments to enterprise-scale deployment within a complex industrial or services environment is required.

Responsibilities

  • Direct a team of 20 or more data scientists and engineers across the full lifecycle of digital products, from prototype to production at scale.
  • Partner with Applied Reliability and Product Service Engineering to define what needs to be done, and with M&D Insights Central to define how it will be done.
  • Define the technical roadmap for AI/ML capabilities, data pipelines, and diagnostics, unified under the Reliability → Analytics → Diagnostics → Closure operating model.
  • Govern model quality, health, and efficacy by minimizing false positives and improving signal-to-noise so teams trust analytics as a primary engineering input.
  • Build, mentor, and retain a world-class team, cultivating technical rigor, curiosity, and rapid experimentation at high quality.
  • Consolidate and modernize diagnostic tooling, eliminating tool sprawl while meeting cybersecurity, data integrity, and engineering standards.
  • Translate technical output into business intelligence that reduces unplanned downtime and increases service value for customers.
  • Champion Lean across the digital workflow, reducing cycle time from model development through deployment.

Desired Qualifications

  • An advanced degree (MS or PhD) in a quantitative discipline such as Data Science, AI/ML, or Operations Research is desired.
  • Experience leading large multidisciplinary technical organizations of 20 or more professionals is desired.
  • Deep expertise in industrial Internet of Things, predictive maintenance, or power generation services is desired.
  • Apply a product mindset to analytics, understanding that models are products that must serve a user and deliver a business outcome.
  • Translate abstract technical challenges into clear strategic priorities for non-technical leadership.
  • Influence cross-functional peers in Engineering and Services to adopt new digital workflows.
  • Practice Lean by applying rigorous process discipline to creative and technical work.
  • Lead with a servant mindset by removing blockers for a specialized team while keeping alignment with the broader business vision.
  • Make data-driven decisions and act decisively despite ambiguity.
  • Bring a One Team mentality by leading horizontally, breaking down silos, and keeping the customer outcome at the center of every decision.

About the Company

GE Vernova

Builds equipment and software for electric power

GE Vernova makes equipment and software that generate and manage electricity for utilities, power producers, and industrial customers. Its Power, Wind, and Electrification businesses span gas turbines, wind generation, and the systems that move electricity across grids. The company supplies generators, grid equipment, and controls, while its software coordinates network operations and integrates changing sources of power. Customers buy equipment and enter service agreements for maintenance, upgrades, and technical support over its operating life, alongside purchases of software and related services. GE Vernova became an independent company in 2024 after separating from GE and is headquartered in Cambridge, Massachusetts.

Company size
10,001+
Company stage
N/A
Total funding
$17.6M
Headquarters
Cambridge, MA
Founded
2024

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