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Data Scientist, Technology Consulting, Digital and Emerging Technologies, Microsoft – Data & AI - Azure Data Scientist (Manager) (Multiple Positions) (1506062), Ernst & Young U.S. LLP, Dallas, TX.
Full time employment, Monday – Friday, 40 hours per week, 8:30 am – 5:30 pm.
MINIMUM REQUIREMENTS:
Must have a Bachelor’s degree in Mathematics, Information Systems, Statistics, Computer Science, Data Science, Machine Learning, Analytics, Engineering or a related field and 5 years of progressive, post-baccalaureate advisory and/or consulting work experience. Alternatively, will accept a Master’s degree in Mathematics, Information Systems, Statistics, Computer Science, Data Science, Machine Learning, Analytics, Engineering or a related field and 4 years of advisory and/or consulting work experience.
Must have 4 years of combined experience with data science, AI, and/or data engineering or big data.
Must have 2 years of combined experience with 3 of the following:
• machine learning such as k-NN, naive bayes, decision trees, or SVM
• data mining and statistical tools
• pattern recognition and predictive modelling
• recommendation engines, scoring systems, A/B testing
• setting up data and experimental platforms
Must have 1 year of experience with analytics and big data technologies within Microsoft Azure, using tools such as Azure Data Factory, Azure Machine Learning, Azure Cognitive Services, Azure
Databricks, or Azure Synapse Analytics.
Must have 1 year of experience with leveraging distributed techniques for training and scoring machine learning models using Azure Databricks.
Must have 1 year of experience with any of the following cloud Machine Learning frameworks and tools such as Tensor Flow, PyTorch, ONNX, Weka, NumPy, or PyMongo.
Must have 1 year of experience with Model Management, such as Azure ML service or MLFlow and deployment of models using Azure Kubernetes Service.
Must have 1 year of experience working in Python, R, Scala, or T-SQL.
Must have 2 years of experience counselling and mentoring junior level consultants by providing structured, on-the-job feedback.
Requires domestic travel up to 70% to serve client needs.
Employer will accept any suitable combination of education, training or experience.
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