Solve complex analytical problems to bring data to insights and enable the use of ML and AI at scale for clients
Assist with clients' data strategy, business priorities, and success measures for designing and building models
Translate business requirements to Data Science solutions leveraging strong business acumen
Apply technical knowledge to architect solutions that meet business needs and AA/AI roadmaps
Collaborate with Microsoft Cloud Solution Architects and Data Platform Engineers on developing complex end-to-end Enterprise solutions on Microsoft Azure platform
Design machine learning pipelines that curate datasets, train, test, validate models, compare model performance, and deploy models
Provide guidance and recommendations around data technology, data models, data storage, and data analytics
Stay abreast of current business and industry trends relevant to the client's business
Manage and motivate teams of professionals with diverse skills and backgrounds
Deliver quality client services by monitoring progress and maintaining long-term client relationships

Requirements

Bachelor's degree in Mathematics, Information Systems, Statistics, Computer Science, Data Science, Machine Learning, Analytics, Engineering or related field and 5 years of progressive advisory and/or consulting work experience
Alternatively, a Master's degree in same fields with 4 years of advisory and/or consulting experience
4 years of combined experience with data science, AI, and/or data engineering or big data
2 years of combined experience with 3 of the following:
- machine learning (k-NN, naive bayes, decision trees, SVM)
- data mining and statistical tools
- pattern recognition and predictive modelling
- recommendation engines, scoring systems, A/B testing
- setting up data and experimental platforms
1 year of experience with analytics and big data technologies within Microsoft Azure (Azure Data Factory, Azure Machine Learning, Azure Cognitive Services, Azure Databricks, Azure Synapse Analytics)
1 year of experience leveraging distributed techniques for training and scoring machine learning models using Azure Databricks
1 year of experience with cloud Machine Learning frameworks and tools (Tensor Flow, PyTorch, ONNX, Weka, NumPy, PyMongo)
1 year of experience with Model Management (Azure ML service or MLFlow) and deployment of models using Azure Kubernetes Service
1 year of experience working in Python, R, Scala, or T-SQL
2 years of experience counselling and mentoring junior level consultants

Benefits

medical and dental coverage
pension and 401(k) plans
wide range of paid time off options
flexible vacation policy
time off for designated EY Paid Holidays, Winter/Summer breaks, Personal/Family Care, and other leaves of absence

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

machine learningdata miningstatistical toolspattern recognitionpredictive modellingrecommendation enginesA/B testingdata engineeringPythonR

Soft Skills

business acumenteam managementclient relationship managementcollaborationmentoring