Quality Statistical Engineering Supervisor:
Corning

23564-en_US
Corning
Corning New York
Healthcare
Apply
Description

Corning is one of the world’s leading innovators in materials science. For more than 160 years, Corning has applied its unparalleled expertise in specialty glass, ceramics, and optical physics to develop products that have created new industries and transformed people’s lives.

Corning succeeds through sustained investment in R&D, a unique combination of material and process innovation, and close collaboration with customers to solve tough technology challenges.

Corning's Manufacturing, Technology and Engineering division (MTE) is recognized as the leader in engineering excellence & innovative manufacturing technologies by providing diverse skills to Corning’s existing & emerging businesses.

We anticipate & provide timely, valued, leading edge manufacturing technologies and engineering expertise.  We partner with Corning’s businesses and the Science & Technology division. Together we create and sustain Corning’s manufacturing as a differential advantage.

Scope of Position:

  • 50% supervision/50% project support
  • Supervision of 5-7 statisticians supporting their project objectives, workload planning and career growth
  • Create vision and strategy for the team
  • Support recruiting efforts
  • Project Support
  • Improving manufacturing capability (e.g. efficiencies, yields, cycle time, and/or material utilization) by identifying and eliminating root cause(s) of variability
  • Problem solving and/or process improvement using a structured methodical approach and appropriate application of statistics (e.g. Six Sigma)
  • Evaluating impact on the product/process from new or existing: raw materials, processes, and/or equipment parameters
  • Evaluating measurement systems to improve quality and/or reduce inspection costs
  • Designing experiments to identify key process inputs/interactions and impact on product
  • Demonstrated experience and strong technical knowledge in data driven and predictive modeling

Day to Day Responsibilities:

  • Ensure proper engagement with direct reports, project teams, and customers
  • Support cross discipline project teams for Research, Development, Engineering, and Manufacturing projects.
  • Apply quality and statistical techniques to solve problems of diverse scope.
  • Exercise judgment in selecting methods and techniques for obtaining solutions. The project portfolio covers a broad range of business areas including Life Sciences, Display Technologies (LCD glass), Environmental Technologies (Automotive and Diesel), Specialty Materials, and Strategic Growth (new business development)

Travel Requirements:

  • Travel will range 10-50% average per year depending on project needs, possible international travel

Hours of work/work schedule/flex-time:

  • 8am-5pm typically

Required Education:

  • MS or PhD in Statistics or Engineering field

Required Years and Area of Experience:

  • 8+ years of experience in Applied Statistics or Quality within manufacturing / R&D environments.

Required Skills:

  • >2years supervisor experience
  • Strong statistical knowledge / experience in these areas: descriptive statistics, inferential statistics, designed experiments, regression and correlation analysis, measurement system analysis
  • Proficiency in the use of computer based statistical applications (e.g. Minitab, SAS, JMP, R, etc.)
  • Ability to influence diverse technical teams
  • Enjoy problem solving in a technical environment with a high level of technical curiosity
  • Ability to present data and analysis in both verbal and written/graphical form that broad audiences can understand

Desired Skills:

  • Statistical knowledge in other areas: nonparametric methods, time series analysis, reliability analysis, multivariate analysis, statistical process control, process capability studies, sample size determination, acceptance sampling, data mining, and comparison tests, data analytics, machine learning.
  • Advanced Excel skills, including pivot table functions and macros
  • Familiarity with OSI-Pi, SQL server queries and using Access databases, Matlab, R
  • Six Sigma Certification - Black Belt
  • Engineering degree

Soft Skills:

  • Must be collaborative and able to openly engage with colleagues to achieve project goals
  • The ability to translate difficult technical concepts to broader audience
  • Self-motivated with an ability to manage one’s own work independently
  • Ability to give and take feedback constructively

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

Basic Qualifications
Requirement