Mechanical Properties Data Analyst & Modeling (Python)

LNN Pace Analytical Life Sciences, LLC; United States; On-site; USD 25,000 - 36,000; Full time

Benefits offered by this job

Medical

Dental

Vision

401K retirement savings plan

Life insurance

Disability insurance

Paid time off

HSA

Wellness program

Tuition reimbursement

Employee Assistance program

Parental leave

ID theft protection

Job summary

Pace is seeking a Mechanical Properties Coding and Modeling technician in the Scientific Insourcing Solutions division. You’ll prepare samples for DMA testing, analyze data, and develop Python-based tools to process results.

Ideal candidates hold a BS in a related field, are familiar with Python in a scientific setting, and can use MS Word/Excel. This is a full-time role with competitive benefits and growth opportunities.

Qualifications

• BS in Chemistry, Physics, Materials Science & Engineering, or related field
• Familiarity with Python in a scientific environment
• Good mechanical aptitude and sample manipulation skills
• Experience with finite element analysis (FEA) preferred
• Familiarity with Microsoft Word and Excel

Responsibilities

• Prepare samples for mechanical analysis by DMA, load frame, peel tester
• Analyze samples by DMA, load frame and peel tester
• Analyze data sets using Python and cloud based tools developed on site
• Develop and modify Python and cloud based data analysis tools
• Follow standard formats procedures for analyzing samples and reporting data
• General lab maintenance duties

Skills

Mechanical testing

Data analysis

Python familiarity

FEA experience

Education

BS in Chemistry, Physics, Materials Science & Engineering, or related field

Tools

Python

Cloud-based data tools

MS Word & Excel

Job description

Pace is seeking a Mechanical Properties Coding and Modeling technician in the Scientific Insourcing Solutions division. You’ll prepare samples for DMA testing, analyze data, and develop Python-based tools to process results.

Ideal candidates hold a BS in a related field, are familiar with Python in a scientific setting, and can use MS Word/Excel. This is a full-time role with competitive benefits and growth opportunities.