Machine Learning Engineer

  • 38997
  • Non-Life - Data Science
  • |
  • Ontario, Canada
  • |
  • Jan 29, 2021
Insurance
RESPONSIBILITIES
  • Work on impactful projects that range from predicting customer life-time values and optimizing customer journeys to incorporating novel data sources for building cutting-edge pricing algorithms
  • Help the team leverage machine learning algorithms to automate and predict claim outcomes and find new and innovative ways to impact our customers.
  • Help build the foundation that enables the team to bring insights to the business and impact millions of customers.
  • Be part of the team that expands the scope of algorithms used in production systems
QUALIFICATIONS
  • A degree in Computer Science/Engineering or related field.
  • 4+ programming experience in Python with strong grasp of software engineering standard methodologies such as code-reusability, modularity, use of repos, etc
  • 3+ years of applied experience in ML, deep learning and NLP
  • Have expert understanding of machine learning and NLP tasks such as classification, feature engineering, information extraction, structured prediction, sentiment analysis, and topic modelling
  • Fully understand different neural networks (LSTM, seq2seq, etc.), different word embedding models and transfer learning.
  • Knowledge of packages such as Tensorflow, Pytorch, Keras, Scikit Learn, Pandas, and NLTK.
  • Proficiency with PostgreSQL, Teradata, Hadoop and AWS is an asset.
  • Experience in a data-driven software engineering environment, with an end-to-end understanding of how to leverage data to make business decisions.
  • A proven track record in building and maintaining high quality, robust and maintainable code.
  • Experience building and working within a Continuous Integration framework.
  • Understanding of Data Warehouse concepts, ETL strategies and best practices.
  • An appetite for problem solving with a creative and resourceful approach to finding the right solution for the job.
  • Strong communication and collaboration skills