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Machine Learning Architect

Toronto, ON
Minimum 6-7 years of relevant work experience.

Masters, PhD, or equivalent experience in a quantitative field (Mathematics, Computer Science, Engineering, Artificial Intelligence, etc.)
Experience in implementing and deploying Machine Learning solutions (using various models, such as Linear/Logistic Regression, Support Vector Machines, (Deep) Neural Networks, Hidden Markov Models, Conditional Random Fields, Topic Modeling, Game Theory, Mechanism Design, etc.)
Experience in AI / ML and data pipeline building (preferred)
Extensive background in statistical analysis and modeling (distributions, hypothesis testing, probability theory, etc.)
Strong hands-on experience with statistical packages and ML libraries (e.g. R, Python scikit learn, Spark MLlib, etc.)
Experience in effective data exploration and visualization (e.g. Excel, Power BI, Tableau, Qlik, etc.)
Experience in developing and debugging in one or more of the languages C#, Scala, Python, or R
Ability to work in cross functional teams
Excellent written and verbal communication skills in English; the ability to convey your message to team members and other stakeholders

Preferred Qualifications

Experience working with relational and NoSQL databases
Familiar with Big Data frameworks (Hadoop or Spark) and cloud infrastructures
Familiar with stream processing frameworks such as Stream Analytics, Kinesis Data Streams, and Kafka Streams
Experience with managed machine learning platforms such as Azure Machine Learning
Experience in applying Machine Learning techniques in the accounting domain
Ability and willingness to multi-task and learn new technologies quickly
 

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