Aerospace Data Scientist: ML for Manufacturing

Howmet Aerospace Inc.; Whitehall Township (MI); On-site; USD 120,000 - 170,000; Full time

Benefits offered by this job

Medical, dental, vision benefits

401(k) with company match

Paid time off

Job summary

Howmet Aerospace Inc. in Whitehall, Michigan is seeking a Data Scientist to join our ML/AI Development Team.

The role focuses on data collection, EDA, model development, deployment support, and cross-functional collaboration to optimize manufacturing processes across casting, alloy, core, and rings facilities. The candidate will build and refine machine learning algorithms, analyze industrial data, and present insights to non-technical audiences while mentoring junior data scientists and

Qualifications

• MS or PhD in a relevant field such as Engineering, Data Science, CS, or Statistics.
• Minimum 5 years of hands-on data science experience with Python.
• Experience applying ML to production or field data in manufacturing.

Responsibilities

• Work with engineering teams to understand challenges and design ML solutions.
• Build and refine ML algorithms to improve products across business units.
• Conduct statistical analyses to improve manufacturing processes.
• Construct, manipulate, and analyze large datasets using Python and SQL.
• Collaborate with IT teams to validate trials and integrate ML into production workflows.
• Present data-derived conclusions to non-technical audiences and mentor data scientists across the organization.

Skills

Data Science

Python

SQL

Machine Learning

Statistics

Communication

Education

MS/PhD in Engineering or Data Science

Tools

Git

Jupyter

Docker

MLflow

Job description

Howmet Aerospace Inc. in Whitehall, Michigan is seeking a Data Scientist to join our ML/AI Development Team.

The role focuses on data collection, EDA, model development, deployment support, and cross-functional collaboration to optimize manufacturing processes across casting, alloy, core, and rings facilities. The candidate will build and refine machine learning algorithms, analyze industrial data, and present insights to non-technical audiences while mentoring junior data scientists and