Date: May 28, 2021
Location: Montreal, Quebec, CA, H4M 2Z2
Please note: iBwave is a wholly-owned subsidiary of 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)
- Detail-oriented and precision
- Team player
SEARCH FIRM REPRESENTATIVES PLEASE READ CAREFULLY
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