Process Data Scientist

Requisition Number: 79606

 

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Corning is one of the world’s leading innovators in glass, ceramic, and materials science. From the depths of the ocean to the farthest reaches of space, our technologies push the boundaries of what’s possible.  ​  

 

How do we do this? With our people. They break through limitations and expectations – not once in a career, but every day. They help move our company, and the world, forward. ​  

 

​At Corning, there are endless possibilities for making an impact. You can help connect the unconnected, drive the future of automobiles, transform at-home entertainment, and ensure the delivery of lifesaving medicines. And so much more.​   

 

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Our Optical Communications segment has recently evolved from being a manufacturer of optical fiber and cable, hardware and equipment to being a comprehensive provider of industry-leading optical solutions across the broader communications industry.This segment is classified into two main product groupings – carrier network and enterprise network. The carrier network product group consists primarily of products and solutions for optical-based communications infrastructure for services such as video, data and voice communications. The enterprise network product group consists primarily of optical-based communication networks sold to businesses, governments and individuals for their own use.

 

Purpose of Position

The Process Data Scientist will serve as an embedded technical partner to process engineering and manufacturing teams, applying traditional statistics, advanced analytics, machine learning, and artificial intelligence to improve process understanding, control, capability, quality, yield, and cost. The role connects rigorous statistical thinking with modern data-science methods to convert manufacturing and quality data into practical, scalable solutions.

The individual will work with data from manufacturing execution systems, measurement and inspection equipment, process-control systems, sensors, ERP systems, and quality systems. Work will range from designed experiments and statistical process control to predictive modeling, anomaly detection, optimization, computer vision, and responsible use of generative AI. The role requires hands-on analysis, close collaboration with process experts, and clear communication of methods, assumptions, uncertainty, and business impact.

This person will be expected to work independently in ambiguous problem spaces, select methods appropriate to the process and data, and help move successful analytical solutions from exploratory analysis into sustained use across manufacturing sites.

 

 

Key Responsibilities

• Partner with process engineering, manufacturing, quality, technology, IT, and data engineering teams to frame business and technical questions as well-defined analytical problems. 

•  Plan, execute, and analyze designed experiments, statistical process control, measurement system analyses, hypothesis tests, and other statistical methods.

•  Analyze manufacturing and quality data to identify sources of variation, quantify relationships among inputs and outputs, establish evidence-based conclusions, and recommend actions. 

•  Develop predictive and prescriptive models using machine learning and statistical techniques for applications such as anomaly detection, predictive maintenance, throughput improvement, process optimization, and defect reduction. 

•  Explore and apply AI capabilities, including computer vision and generative AI, in a manufacturing setting.

•  Use Python, SQL, and big-data platforms including Databricks to prepare data, engineer features, build reproducible analyses, and work effectively with large and complex datasets. 

•  Collaborate with data engineering and IT partners to define analysis-ready datasets, data-quality checks, contextual data requirements, and scalable analytical workflows. 

•  Create dashboards, reports, visualizations, and technical summaries that communicate process performance, analytical findings, limitations, and recommended actions to technical and non-technical stakeholders. 

•  Develop reusable analytical methods, code, templates, and standards that improve consistency across sites and reduce duplicated effort. 

•  Train and coach engineers and other stakeholders in statistical thinking, data interpretation, and appropriate use of advanced analytics and AI. 

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

 

 

Required Qualifications

•  Bachelor’s degree in Data Science, Computer Science, Statistics, or a related field.

•  3+ years of experience in data science, statistics, or a related field, preferably in a manufacturing or industrial setting.

•  Proficiency in Python and SQL, with experience using big data platforms (e.g., Databricks, Spark, and Hadoop).

•  Strong foundation in statistical modeling, machine learning, and data mining techniques.

•  Advanced data visualization skills using Power BI, Tableau, or similar tools.

•  Excellent communication and leadership skills with the ability to influence at all levels of the organization.

 

 

Preferred Qualifications

•  Master’s degree or Ph.D. in a data-related field, such as statistics, data science, computer science, or a related discipline.

•  Experience with manufacturing systems (MES, ERP) and industrial data platforms (e.g., OSI PI).

•  Familiarity with MLOps practices and tools for model deployment and monitoring.

•  Experience with JMP and/or Minitab statistical software.

•  Knowledge of Lean Six Sigma, quality engineering, process improvement, and Manufacturing 4.0 concepts. 

•  Bilingual or multilingual capability and experience working with global teams.

 

 

Soft Skills

•  Strong collaborator who can build productive relationships with process experts and cross-functional partners. 

•  Curious and hypothesis-driven, with the judgment to distinguish correlation, prediction, and causation. 

•  Self-motivated and able to define a path forward with limited direction. 

•  Comfortable balancing analytical rigor, speed, practical constraints, and business value. 

•  Able to challenge assumptions constructively and communicate limitations transparently. 

•  Able to train, coach, and influence others in statistical and data-driven thinking. 

•  Detail-oriented, with a strong focus on accuracy, reproducibility, documentation, and follow-through. 

 

 

Travel Requirements

•  Up to 20%, including international travel to support global teams and initiatives.

•  Normal business hours are expected, with flexibility to collaborate across regions and time zones as needed. 

 

 

This position does not support immigration sponsorship.  

 

The range for this position is $91,311.00 - $125,553.00 assuming full time status. Starting pay for the successful applicant is dependent on a variety of job-related factors, including but not limited to geographic location, market demands, experience, training, and education. 

 

A job that shapes a life.  

Corning offers you the total package.  

 

We prohibit discrimination on the basis of race, color, gender, age, religion, national origin, sexual orientation, gender identity or expression, disability, veteran status or any other legally protected status.

 

Corning is committed to providing equal employment opportunities and considers requests for reasonable accommodations in accordance with applicable laws. Individuals with disabilities or sincerely held religious beliefs may request reasonable accommodations to participate in the application or interview process, perform essential job functions, or access other benefits and privileges of employment. To submit a request for reasonable accommodation related to disability or religion, please contact us at accommodations@corning.com.