Data Scientist, Engineering Analytics for AI Systems

Amphenol Communications Solutions; Yocumtown (PA); On-site; USD 90,000 - 150,000; Full time

Job summary

Amphenol Communications Solutions (ACS) is seeking a Data Scientist in Etters, PA to apply statistical modeling and machine learning to engineering data. You will work with data analysts and software engineers to turn data into actionable insights that guide design and manufacturing decisions.

The role requires 3+ years of data science experience, strong ML knowledge, and the ability to communicate complex methods to both technical and non-technical stakeholders.

Qualifications

• 3+ years of experience in a data science or applied statistics role.
• Bachelor’s degree required; MS or PhD preferred.
• Strong statistical and ML knowledge; able to handle messy real-world data.
• Excellent communication skills to explain complex methods to non-technical stakeholders.

Responsibilities

• Design and build statistical and machine learning models to solve engineering problems.
• Partner with engineering stakeholders to scope analytical projects.
• Explore and analyze large, complex datasets to uncover patterns.
• Collaborate with data analysts and software engineers to productionize models.
• Validate model performance and monitor models in production.
• Communicate findings clearly to technical and non-technical audiences.
• Stay current on statistical and ML techniques and assess applicability.

Skills

Statistical methods

Machine learning

Data wrangling

Communication

Education

Bachelor's degree in Data Science, Statistics, Applied Mathematics, Computer Science, or related field

MS or PhD preferred

Tools

Python

SQL

Job description

Amphenol Communications Solutions (ACS) is seeking a Data Scientist in Etters, PA to apply statistical modeling and machine learning to engineering data. You will work with data analysts and software engineers to turn data into actionable insights that guide design and manufacturing decisions.

The role requires 3+ years of data science experience, strong ML knowledge, and the ability to communicate complex methods to both technical and non-technical stakeholders.