Remote Head of Data Science & ML for Metals Manufacturing

Precision Castparts Corp.; United States, Northern America, Americas; À distance; USD 135 000 - 155 000; Plein temps

Résumé du poste

Precision Castparts Corp. seeks a Head of Data Science and Machine Learning to lead data innovation across PCC Metals and Forgings Technology. You will develop analytics, build digital twins, and guide AI-driven decisions that connect processing variables to quality outcomes.

The role blends mentorship with hands-on leadership on cross-disciplinary teams. You will shape models, ensure statistical rigor, and advance automation and digitalization efforts in a dynamic manufacturing environment with

Qualifications

• MS/PhD in Materials Science or related engineering is required or preferred.
• 10+ years of experience in data science, ML, and manufacturing contexts.
• Strong background in ML, AI, computational methods and data modeling.

Responsabilités

• Develop and execute data innovation strategy within Metals and Forgings Technology Function.
• Lead data pipelines, data mining, ML/AI, and data modeling plans for projects.
• Drive Industry 4.0 initiatives from pilot to scale-up.
• Mentor automation and modeling engineers; enable linkages between processing variables and quality outcomes.
• Deliver analytics that improve financial and process metrics on the shop floor.

Connaissances

Scripting automation

Finite element modeling

TensorFlow/PyTorch/Keras

Systems thinking

Communication

Teamwork

Independence

Formation

MS/PhD in Materials Science or related engineering

10+ years experience

Outils

Python

MATLAB

R

C

C++

Fortran

Visual Basic

DEFORM

Abaqus

ANSYS

CATIA

AFGROW

ABAQUS

TensorFlow

Description du poste

Precision Castparts Corp. seeks a Head of Data Science and Machine Learning to lead data innovation across PCC Metals and Forgings Technology. You will develop analytics, build digital twins, and guide AI-driven decisions that connect processing variables to quality outcomes.

The role blends mentorship with hands-on leadership on cross-disciplinary teams. You will shape models, ensure statistical rigor, and advance automation and digitalization efforts in a dynamic manufacturing environment with