Data Scientist: Engineering Analytics & ML

Amphenol Communications Solutions; Yocumtown (PA); On-site; USD 90,000 - 130,000; Full time

Job summary

Amphenol Communications Solutions (ACS) seeks a Data Scientist to apply statistical modeling, ML, and analytics to engineering data. You will work with data analysts and software engineers to solve complex problems and provide insights guiding engineering decisions.

You will design models to predict failures, optimize processes, and identify trends, collaborating with stakeholders to translate questions into analytical projects and ensuring models run in production with ongoing monitoring.

Qualifications

• Bachelor's degree in Data Science, Statistics, Applied Mathematics, CS or related field required.
• Solid understanding of statistical methods and ML techniques.
• Experience with messy, real-world data and cross-source validation.
• Strong communication to explain methods to non-technical stakeholders.

Responsibilities

• Design and build statistical and ML models to solve engineering problems.
• Partner with engineering stakeholders to scope analytical projects.
• Explore large datasets to uncover patterns and insights.
• 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 stakeholders.
• Stay current on techniques and evaluate applicability to engineering problems.

Skills

Statistics & ML understanding

Data cleaning & validation

Communication skills

Education

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

MS or PhD preferred

Tools

Python (scikit-learn, pandas, numpy)

SQL

Job description

Amphenol Communications Solutions (ACS) seeks a Data Scientist to apply statistical modeling, ML, and analytics to engineering data. You will work with data analysts and software engineers to solve complex problems and provide insights guiding engineering decisions.

You will design models to predict failures, optimize processes, and identify trends, collaborating with stakeholders to translate questions into analytical projects and ensuring models run in production with ongoing monitoring.