Purpose of the Position:
As a leading manufacturing and technology company, Corning manufacturing systems generate a vast amount of process and product data through advanced control and measurement systems. The data analytic engineer position will be responsible for transforming these valuable data assets into deep insights into the manufacturing process, and help different Corning businesses to improve their manufacturing processes or design new ones for our long-term success. In parallel, the data analytics engineer will work with a global multifunctional team to advance Corning’s Smart Manufacturing strategy with the state-of-art technologies (such as advanced analytics, machine learnings, etc.).
Day to Day Responsibilities:
- Select, evaluate and implement appropriate analytics tools and options (ie. statistics methods or machine learning techniques) to perform exploratory and targeted data analysis and apply the findings to process measurement and control solutions.
- Act as an expert in data analytics field to develop and customize algorithms as necessary to meet Corning’s business requirements on existing or new processes.
- Evaluate and demonstrate quantifiable impact on the raw materials, finished product, manufacturing process and manufacturing supporting systems through the use of data analytics and data visualization tools (e.g. Tableau, Power BI … etc).
- Write technical reports summarizing development, application, and validation of the technical analysis.
- Share and contribute Corning’s data analytics community of practice in developing the capabilities and promoting areas of applications.
- Support senior data analytics engineer in delivery of basic and advanced data analysis courses in the organization and provide technical consultancy to wide spectrum of user groups within company.
Education & Experience
- Minimum MS Degree (PhD preferred) in applied mathematics, statistics, computer science or a comparable field of study with specialization in data analytics & machine learning.
- 1-3 year of work experience in similar field, analytical algorithms development or modeling experience.
- Be well acquainted in dealing with mathematical & statistical algorithms (e.g. regression, Bayesian models and numerical optimization etc.) and machine learning techniques (e.g. clustering, classification and neural networks etc.)
- Data Analysis knowledge using any mix of software including, but not limited to: JMP, MATLAB, R, Minitab, SAS.
- Working knowledge of programming in Python.
- Ability to analyze, optimize and debug scientific code.
- Able to work with complex databases.
- Experience compiling and running code on high-performance computers.
- Knowledge of machine learning libraries (such as Tensor Flow, Keras, CNTK, Theano, SciKit-learn, Torch).
- Proficiency in Statistical Methods including DOE, Hypothesis Testing, Inferential Statistics, ANOVA, Multivariate Analysis, Linear and Non-linear models and Regression Analysis
- Basic understanding of Big Data technologies (such as Hadoop, Spark, etc) and Cloud solutions
- Strong mathematical and programming skills and capability for independently preparing data (ETL functions of cleaning, consolidating, transforming data) for machine learning purposes.
- Ability to bridge gaps between “domain” language (engineering, science) and “computing solution” language.
- Ability to support multiple projects concurrently.
- Maintain technical curiosity and willingness to learn with strong problem solving and analytical skills.
- Must be collaborative and able to openly engage multinational interdisciplinary team to achieve project goals.
- Ability to communicate effectively by phone and video with team members in international locations.
- Clear dedication to excellence and advancing beyond the current state.
- Self-motivated with an ability to manage one’s own work with minimum supervision.