Data Scientist - Metrology

Overview
At US Conec, we're proud to be a global leader in high-density fiber-optic connector solutions, drawing on over 30 years of precision engineering, injection molding, and plastics manufacturing expertise.

We’re seeking a Data Scientist – Metrology to apply advanced analytics, statistics, and machine learning techniques to metrology challenges. You’ll help design and validate products, improve process control, and unlock insights from complex measurement data. Whether you’re an experienced professional or a recent graduate eager to grow, this role offers a unique opportunity to bridge data science and precision engineering.

Responsibilities

· Analyze metrology datasets to identify trends, improve accuracy, and optimize manufacturing efficiency.

· Develop and maintain statistical models, monitoring systems, and predictive algorithms.

· Design experiments and analyze results using statistical tools (Excel, Minitab, MATLAB, Python, R, etc.).

· Collaborate with engineers to troubleshoot quality issues and propose data-driven corrective actions.

· Support creation of fixtures, automation routines, and measurement programs for ferrule and mold validation.

· Document test plans, results, and analyses, and contribute to technical reports or patent filings.

· Manage databases and reporting systems to ensure accessible, reliable data measurement.

· Stay current with new metrology tools, image processing, and advanced analysis methods.

Requirements

Must Haves

· Bachelor’s degree in Data Science, Metrology, Engineering, Applied Mathematics, or a related discipline

· Strong background in statistics, data modeling, and analysis

· Ability to plan, execute, and interpret experiments

· Solid foundation in mechanical design and principles

· Proficiency with at least one data-analysis tool or language (e.g., MATLAB, Python, R, Minitab, Excel)

· Strong communication and problem-solving skills

Nice to Haves

· Experience with optical metrology, image processing, or CAD tools

· Familiarity with automation, robotics, or automated test systems

· Exposure to machine learning or AI-driven analysis methods