Predictive Maintenance Data Scientist at Corning Incorporated in Corning, NY
Corning is the world leader in specialty glass and ceramics, building and manufacturing keystone components that enable high-technology systems. Corning's history is filled with breakthrough technologies that have played a meaningful role in the way the world works. We thrive on solving difficult, commercially relevant problems through a creative and collaborative research and development process. Corning succeeds through sustained investment in R&D, more than 160 years of materials science and process engineering knowledge, and a distinctive reciprocal culture. Corning's Manufacturing, Technology and Engineering division (MTE) is recognized as the leader in engineering perfection & 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 build and sustain Corning's manufacturing as a differential advantage. Key
Responsibilities:
Successfully identify the real problem from the customer's point of view to build and execute predictive maintenance work plans that deliver business impact. Communicate technical analyses and results to division customers. Perform exploratory and targeted data analysis using commercial and open source data analytic software packages. Apply multivariate statistical methods and machine learning techniques to find structure and value in both large and small data sets to identify key process input variables that can feed process control solutions. Develop predictive/classification models for use in production and possible applications. Write technical reports summarizing development, application, and validation of the technical analysis. Travel Requirements:
Travel requirements will vary. Expected travel up to 25% both Domestic and International. Required Education:
BS in an Engineering discipline with 5
years' experience (or MS in an Engineering discipline with 3
years' experience) working in a data analytics or software intensive environment. Experience with Data Science areas such as Statistics, Advanced Analytics, Data Preprocessing and Machine Learning is a MUST. Technical experience with software tools and languages:
Anaconda, Python, Matlab, C/C++/C#, SQL. Completion of Data Science bootcamps and/or certifications. Software development background with Agile and CI/CD approaches. Required Skills:
Your ability to show the relevance of the applied techniques in machine learning and Predictive Maintenance. Prioritizing work across multiple projects will be critical. Serve as an Analytics Translator for multiple business groups by understanding the business need and determining how analytics can help projects and businesses achieve their goals. Identify analytics and ML opportunities, build internal proposals, and gain stakeholder buy-in. Work with senior data scientists to develop and grow the overall predictive maintenance analytics capability of the company. Your passion, knowledge of, and experience applying multivariate statistical analysis algorithms including intelligent automation techniques for classification, regression, and clustering. Demonstrated experience with visualization tools (i.e. SAS JMP, Power BI, Tableau). Strong attention to detail and organizational skills. Ability to work collaboratively in a team environment across stages of innovations. Ability to communicate the outcome of complex and/or technical concepts in a clear manner to a non-analytical group and take on challenges specific to analyzing disparate data sources. Transition proof-of-concept analysis and models into deployed production applications. Desired Skills:
Familiarity with ETL tools for data extraction, data cleansing, and data manipulation. Experience applying time series and frequency-based analysis and modeling (i.e. ARIMA, Fourier analysis). Software version control experience (i.e. Git, Gitlab/GitHub). Knowledge and experience with DevOps tools such as CI/CD. Knowledge of deep learning techniques (i.e. CNN, RNN) and software packages such as TensorFlow, Keras, etc. Familiarity with big data ecosystem (Spark, Hadoop, HIVE, etc.) and cloud-based storage and compute environments (AWS, MS Azure). Software development experience in C, C++, and/or C#.
Salary Range:
$80K -- $100K
Minimum Qualification
Data Science & Machine Learning, Electrical EngineeringEstimated Salary: $20 to $28 per hour based on qualifications.
Responsibilities:
Successfully identify the real problem from the customer's point of view to build and execute predictive maintenance work plans that deliver business impact. Communicate technical analyses and results to division customers. Perform exploratory and targeted data analysis using commercial and open source data analytic software packages. Apply multivariate statistical methods and machine learning techniques to find structure and value in both large and small data sets to identify key process input variables that can feed process control solutions. Develop predictive/classification models for use in production and possible applications. Write technical reports summarizing development, application, and validation of the technical analysis. Travel Requirements:
Travel requirements will vary. Expected travel up to 25% both Domestic and International. Required Education:
BS in an Engineering discipline with 5
years' experience (or MS in an Engineering discipline with 3
years' experience) working in a data analytics or software intensive environment. Experience with Data Science areas such as Statistics, Advanced Analytics, Data Preprocessing and Machine Learning is a MUST. Technical experience with software tools and languages:
Anaconda, Python, Matlab, C/C++/C#, SQL. Completion of Data Science bootcamps and/or certifications. Software development background with Agile and CI/CD approaches. Required Skills:
Your ability to show the relevance of the applied techniques in machine learning and Predictive Maintenance. Prioritizing work across multiple projects will be critical. Serve as an Analytics Translator for multiple business groups by understanding the business need and determining how analytics can help projects and businesses achieve their goals. Identify analytics and ML opportunities, build internal proposals, and gain stakeholder buy-in. Work with senior data scientists to develop and grow the overall predictive maintenance analytics capability of the company. Your passion, knowledge of, and experience applying multivariate statistical analysis algorithms including intelligent automation techniques for classification, regression, and clustering. Demonstrated experience with visualization tools (i.e. SAS JMP, Power BI, Tableau). Strong attention to detail and organizational skills. Ability to work collaboratively in a team environment across stages of innovations. Ability to communicate the outcome of complex and/or technical concepts in a clear manner to a non-analytical group and take on challenges specific to analyzing disparate data sources. Transition proof-of-concept analysis and models into deployed production applications. Desired Skills:
Familiarity with ETL tools for data extraction, data cleansing, and data manipulation. Experience applying time series and frequency-based analysis and modeling (i.e. ARIMA, Fourier analysis). Software version control experience (i.e. Git, Gitlab/GitHub). Knowledge and experience with DevOps tools such as CI/CD. Knowledge of deep learning techniques (i.e. CNN, RNN) and software packages such as TensorFlow, Keras, etc. Familiarity with big data ecosystem (Spark, Hadoop, HIVE, etc.) and cloud-based storage and compute environments (AWS, MS Azure). Software development experience in C, C++, and/or C#.
Salary Range:
$80K -- $100K
Minimum Qualification
Data Science & Machine Learning, Electrical EngineeringEstimated Salary: $20 to $28 per hour based on qualifications.
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