Designing and implementing machine learning algorithms to forecasting, planning and localization
o Fine tuning existing models (deep learning and neural networks) by refactoring code and enhancing to be integrated into ML pipelines
o Building clustering solutions for localization
o Designing and developing unit tests and validations for the model outputs
o Integrating tests into the production pipelines
o Developing new features to improve model performance
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Masters degree in Machine Learning, Computer Science, Information Technology, Operations Research, Statistics, Applied Mathematics, Econometrics, or related field.
o 5 years' experience in data science, machine learning, optimization models, or related field.
o Experience with data cleaning, preparation, and featurization and selection techniques.
o Soid experience with Python, Spark
o Hands-on experience with Python, Java or Scala, and the ability to write reusable and efficient code to automate machine learning pipelines and data processes
o Experience using open source frameworks (for example, scikit learn, tensorflow, torch).
o Experience with forecasting methodologies
o The ability to work in a fast-paced, deadline-driven environment.
Benefit packages for this role will start on the 31st day of employment and include medical, dental, and vision insurance, as well as HSA, FSA, and DCFSA account options, and 401k retirement account access with employer matching. Employees in this role are also entitled to paid sick leave and/or other paid time off as provided by applicable law.