Share this Job

Enterprise Data Scientist

Apply now »

Date: Mar 1, 2019

Location: Painted Post, NY, US, 14870

Company: Corning

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.

The global Information Technology (IT) Function is leading efforts to align IT and Business Strategy, leverage IT investments, and optimize end to end business processes and associated information integration technologies.  Through these efforts, IT helps to improve the competitive position of Corning's businesses through IT enabled processes.  IT also delivers Information Technology applications, infrastructure, and project services in a cost-efficient manner to Corning worldwide. 


This role is part of Data Labs that is a fast pace agile advanced data analytics environment for identifying value in data and experimenting towards development of hypothesis, models and industrial strength data pipelines and solutions. We partner with different teams to implement and execute on Corning’s Digital Transformation goals.


Enterprise Data Scientist / Sr. Advanced Analytics Engineer will discover information hidden in various data sets across the enterprise in manufacturing, supply chain, commercials, finance, human resources and other functions. The data scientist will develop hypothesis, conduct experiments, build models and refine them to address use cases and solve various problems.

Scope of Position: Primary objective is to use data analysis, statistics, modelling and machine-learning skills to curate data and build models to solve various technical and business problems. The candidate should have clear understanding of statistics, modelling and machine learning concepts and have experience with capturing data with different tools, analyzing them with different frameworks and modelling them using various algorithms and techniques. With a research and experimentation mindset, candidate should be able to choose the most appropriate approach, and articulate characteristics of final models.

Roles & Responsibilities:

  • Explore and analyze data using commercial and open source analytics packages
  • Apply multivariate statistical methods and supervised, unsupervised, and reinforcement machine learning techniques
  • Based on characteristics of data set, individually or in collaboration with other data scientists/experts, identify features and fine tune models.
  • Evolve models from development to production and within production environments.
  • Understand problems from customer’s experience point of view, understand application of models in the context of business problems and deliver to meet customer goals or to delight customers.
  • Articulate analyses and results with willingness to share and to learn via sharing.
  • Write technical reports summarizing your work.
  • Evaluate various models, libraries, work benches, tools, as needed

Education & Experience Requirements:

  • MS with 10 years of experience or PhD with 5 years of experience in Computer Science, Statistics, Mathematics, Physics, Engineering or other quantitative disciplines
  • Exceptional candidates with fewer years of experience will be considered

Required Skills:

  • Experience with structured, semi-structured and unstructured datasets in static and streaming modes representing time series data, event driven data or batch data with variations in time, space and features.
  • Experience applying multivariate statistical analysis algorithms including machine learning techniques for classification, regression, and clustering. Techniques for example, but not limited to decision trees, random forest, SVM, logistic regression, neural networks, k-means clustering, Bayesian models, etc.
  • Experience with ANOVA, DoE and SPC methods and techniques - Experience with toolkits and frameworks such as scikit-learn, R, NumPy, SciPy, Matlab, Azure machine-learning studio, AWS Machine Learning, TensorFlow, Keras, etc. In-depth expertise in at least two of these.
  • Experience with SQL and relational databases as well as NoSQL databases such as MSSQL, Hive, HBase, Cassandra, MongoDB including data structure, querying and visualization.
  • Experience with developing software using various programming languages such as Python, Scala, R, JavaScript, Java, .NET
  • Experience transitioning PoCs and models into deployed / production applications
  • Ability to articulate and communicate complex and/or technical concepts clearly to non-analytical teams
  • Ability to communicate effectively by phone and video with team members in remote and/or international locations
  • Must be a self-starter with ability to collaborate on research and work with high-performing teams on several projects simultaneously

Desired Skills:

  • Experience with big data stacks such as MapR, HortonWorks and Cloudera, and Spark.
  • Experience working in agile/scrum mode and/or in startups

Travel: Ability to travel up to 25% to domestic or international locations

This position does not support immigration sponsorship.

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.

Nearest Major Market: Corning