Data Analytics Engineer, Corning Incorporated

Responsibilities:

Work with project teams to solve manufacturing/business problems using machine learning;
Lead measurement development to deliver low-cost inspection systems;
Construct graphical representations of data & data summaries to provide insight to stakeholders;
Use image analytics & text analytics to construct predictive models of process outcomes;
Create model interpretability & engineering tools using techniques including saliency mapping & interactive model profilers;
Work with software developers to implement machine learning models in production environments.
Up to 10% domestic & international travel.

Master’s in Computer Science, Statistics, Analytics, Data Science, or related field with concentration or coursework in data science or machine learning.
1 year of exp. using machine learning & data science to deliver manufacturing solutions for new process development & quality systems.
1 year of exp with model interpretability (i.e. saliency mapping, model profiling);
Using long & wide data analysis methods to manage & manipulate large data sets;
Applying machine learning regularization techniques & cross-validation strategies to classify regression issues, incl. gradient boosting & neural networks;
Using classical programmatic image feature engineering for image recognition, incl. convolutional neural networks, transfer learning, sub-image semantic labeling, & deep clustering;
Developing & implementing machine learning solutions using Python;
Using IATF 16949 to develop automotive quality management systems.