Data Analyst

Purpose of Position

The Data Analytics Engineer will serve as an embedded analytics partner to process engineering teams, with primary responsibility for applying statistical analysis, data visualization, and data-driven problem solving to manufacturing and engineering challenges. This role will support Corning’s Reynosa region in the Optical Connectivity Solutions Division and interface globally, with a focus on helping manufacturing measure process performance, identify opportunities for improvement, and improve process control through effective use of data.

The role will primarily support multifiber connectorization processes within Corning’s data center business. The hire will work with manufacturing and quality data, especially manufacturing execution system data and part quality data from measurement equipment, to generate insights that support process understanding, operational improvements, and data-driven decision-making. The primary emphasis is on analytics, statistical thinking, and data visualization along with elements of machine learning, AI, and data engineering.

This individual will be expected to work independently in ambiguous problem spaces, partner closely with process engineers and other cross-functional stakeholders, and communicate findings clearly to technical and business audiences. In practice, the role will include both project-based analytical work and the development of dashboards and standardized reporting.

Key Responsibilities

• Perform statistical analysis and interpret results to support manufacturing and engineering process improvement.

• Partner closely with process engineers as an embedded analytics resource to investigate process behavior, document performance, and identify opportunities to reduce variability and improve control.

• Prepare, clean, and organize data for analysis, including basic transformation and structuring of data from multiple sources.

• Analyze existing manufacturing and quality datasets, with emphasis on MES data and part quality data from measurement systems.

• Apply appropriate statistical methods to solve process and quality problems and to support hypothesis-driven investigations.

• Develop dashboards, reports, and visualizations to communicate process performance and analytical findings to stakeholders.

• Contribute to advance analytics solutions in machine learning, AI, and computer vision

• Support teams in leveraging data more effectively to monitor processes, identify trends, and enable data-driven decision-making.

• Contribute to the development of standardized reporting and analytics approaches across sites and teams where appropriate.

• Collaborate with cross-functional partners in engineering, manufacturing, quality, and other functions to understand needs and deliver practical analytical solutions.

• Train and coach stakeholders on data usage, reporting tools, and interpretation of analytics results to build organizational capability.

• Deliver value in environments where problems may be loosely defined and data may be incomplete, requiring initiative, sound judgment, and attention to detail.

Required Qualifications

• Bachelor’s degree in Statistics, Data Science, Mathematics, Computer Science, Industrial Engineering, or a related technical discipline.

• Approximately 3+ years of relevant experience in data analytics, statistical analysis, manufacturing analytics, process engineering analytics, or a related field.

• Strong knowledge of statistics, data analysis, and analytical problem solving.

• Strong SQL skills for data extraction, transformation, and analysis.

• Strong Python skills for data analysis, visualization, and related workflows.

• Experience creating data visualizations, dashboards, and reports to support decision-making.

• Ability to work effectively with manufacturing and quality data.

• Ability to prepare, clean, and structure data for analysis.

• Basic knowledge of data engineering concepts and data workflows.

• Strong written and verbal communication skills in English.

• Ability to explain analytical findings clearly to technical and non-technical stakeholders.

• High attention to detail and strong organizational skills.

Preferred Skills

• Direct manufacturing experience strongly preferred.

• Experience with Databricks strongly preferred.

• Experience with Power BI for dashboarding and reporting.

• Experience with JMP for statistical analysis and visualization.

• Familiarity with machine learning methods and their practical application in business or manufacturing settings.

• Familiarity with LLMs, AI tools, or emerging analytics technologies.

• Understanding of statistical process control (SPC), variation reduction, and manufacturing performance metrics.

• Experience integrating or analyzing data from MES, quality systems, and measurement equipment.

• Understanding of manufacturing processes and industrial data systems.

Soft Skills

• Strong collaborator who can work closely with process engineers and cross-functional teams to solve problems.

• Self-motivated and able to work independently with limited direction.

• Comfortable operating in ambiguous environments and defining a path forward.

• Able to train, coach, and influence others in the use of analytics and data-driven thinking.

• Strong communication and presentation skills, including the ability to work effectively across countries, teams, and cultures.

• Detail oriented, with a strong focus on accuracy, data integrity, and follow-through.

Travel/Working Hours

• Travel up to 25% of the time, domestically and internationally.

Normal business hours are expected with flexibility to meet with other regions as needed