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Machine Learning Engineer, Time Series Predictive Modeling

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Date: Oct 20, 2021

Location: Montreal, Quebec, CA, H4M2Z2

Company: Corning

As a Fortune 500 leader in advanced glasses and ceramics development for over a century, Corning Inc overcomes challenging engineering problems continually. The Advanced Analytics and Machine Learning Group within the Corning Technology Center, Montreal (CTCM) is a team of scientists, engineers and software developers working on broad-spectrum machine learning and data science solutions to enable some of the most exciting industrial innovations of our time. 


WHAT YOU WILL BE DOING 

 

We are looking for a talented and motivated Machine Learning and Analytics Engineer focusing on applications involving forecasting in the time domain. You will provide technical leadership in a variety of Corning initiatives involving predictive modeling for sequence and time series data. 


SCOPE OF THIS POSITION 

 

  • Develop time series predictive models for a range of application areas spanning R&D, Manufacturing, Finance and Supply Chain Management. 
  • Work on all aspects of the analytics solution development from building efficient data pipelines to implementing leading-edge inferential methods.
  • Deploy scalable solutions for large datasets
  • Develop high-quality code for analytics software solutions, primarily with the Python data-science stack, and using compiled languages such as C/C++/C#/Java when required. 
  • Work in collaboration with project management to deliver effective and timely solutions. 
  • Interact regularly with research groups within Corning. 
  • Stay abreast of new developments in the field of time series modeling and forecasting, with a constant eye on how these innovations can be applied to our problems. 
  • Participate in presenting new results and research innovations internally and externally. 
  • Cultivate and grow ties with academia.
  • Mentor interns and new hires. 

WHAT WE ARE LOOKING FOR if you have it, let’s talk.

 

  • Strong background in developing time series predictive models using classical as well emerging machine learning methods.  
  • Experience demonstrated through industrial work, academic research projects, compelling open-source project contributions or an impressive Kaggle scoreboard. 
  • Deep understanding of both point forecasts and estimation of uncertainty distribution for hierarchical time domain data sets. 
  • Strong programming background in one or more languages such as Python, C++, C#, Java, Scala.
  • Excellent communication skills – both oral and written.
  • At least an undergraduate degree in Engineering, Computer Science, Math, Statistics, Physics. Advanced degree is an asset. 
  • Strong hands-on experience with the Python data science stack (Python core, NumPy, SciPy, Pandas, Matplotlib, scikit-learn and deep learning frameworks such as Tensorflow or PyTorch). 
  • Experience in writing clean and maintainable code is critical. Working as part of a team using source management frameworks such as GIT is a strong asset. 
  • Familiarity with platforms for doing data science at scale, such as Apache Spark or Dask is an asset. 

 

DESIRED SOFT SKILLS

 

  • Autonomy (Self-starter)
  • Creativity
  • Detail-oriented and precision
  • Team player
  • Organized

 

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