Remote-ready AI/ML Engineering Lead for Power & Utilities

EY; Hoboken (NJ); Híbrido; USD 126.000 - 230.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Hybrid work model

Competitive compensation

Generous time‑off and holidays

Descripción de la vacante

EY is seeking a Manager in AI Native Engineering to lead diverse teams delivering scalable AI/ML solutions for Power & Utilities clients. You will guide data science, software engineering, and analytics across cloud and on‑prem environments to industrialize analytics and drive business value.

You will work with regulated utilities, advise on data governance, and ensure model risk management while delivering client‑facing leadership and technical excellence.

Formación

• Requires a 4‑year Bachelor’s degree; Master’s preferred for advanced roles.
• 6–10 years of experience in AI/Data Science/MML; 2–4 years leading technical teams.
• Strong Python, ML, and cloud skills; experience with DevOps and CI/CD pipelines.

Responsabilidades

• Lead workstreams; manage processes and projects effectively.
• Improve processes through research and analysis of innovative solutions.
• Oversee professional staff; ensure performance and results across complex initiatives.
• Engage with clients; drive sessions from planning to closure.
• Identify opportunities for additional services and manage engagement economics.
• Translate AI/analytics outputs into business insights for executives and operators.

Conocimientos

Python

AI/ML

Data science

Team leadership

Client engagement

Cloud computing

Educación

Bachelor's degree

Master's degree preferred

Herramientas

GIT

Azure DevOps

Jira

SQL

Spark

Descripción del empleo

EY is seeking a Manager in AI Native Engineering to lead diverse teams delivering scalable AI/ML solutions for Power & Utilities clients. You will guide data science, software engineering, and analytics across cloud and on‑prem environments to industrialize analytics and drive business value.

You will work with regulated utilities, advise on data governance, and ensure model risk management while delivering client‑facing leadership and technical excellence.