$80K — $100K *
EY is investing significantly in the build out of Data and AI services that leverage Microsoft Azure. This is a rapidly growing area, and you will have the opportunity to lead and develop your skill set to keep up with the ever-growing demands of the data science landscape. As a key leader within the firm, you will help our clients navigate the complex world of modern data science and analytics. You will provide our clients with a unique perspective on how data science and analytics can transform & improve their entire organization – starting with key business issues they face. This is a high growth, high visibility area with plenty of opportunities to enhance your skillset and build your career.
Your key responsibilities
As an Azure Data Scientist, Senior, you will be focusing on developing solutions and working in client engagement teams, working with a wide variety of clients to deliver tech consulting services with a focus on designing and building machine learning models.
Skills and attributes for success
Understanding clients’ data strategy, business priorities, and success measures to provide context for designing and building models.
Translating business requirements to Data Science solutions leveraging strong business acumen.
Applying technical knowledge to architect solutions that meet business needs, AA/AI roadmaps, and contributing to architectures that enable the ability to scale to support additional modelling use cases (e.g. Azure ML, Azure Data Lake, Azure Databricks, Azure Data Factory, Azure Synapse Analytics, Azure SQL, Azure EventHub/IoT Hub, etc.)
Collaborating with Microsoft Cloud Solution Architects and Data Platform Engineers in developing complex end-to-end Enterprise solutions on Microsoft Azure platform.
Designing machine learning pipelines that curate datasets, train, test, and validate models, compare model performance to existing or previously catalogued models, and then package the models and either deploy them to a real-time serving layer or handle batch scoring activities.
Foster collaboration between DevOps and data science teams within organizations to build MLOps practices
Ability to conduct data profiling, cataloguing, and data mapping for technical design using a use case-based approach that drives the construction of technical data flows.
Participating in large-scale client engagements. Fostering relationships with client personnel at appropriate levels. Consistently delivering quality client services. Driving high-quality work products within expected timeframes and on budget.
Monitoring progress, managing risk and ensuring key stakeholders are kept informed about progress and expected outcomes.
Provides directional guidance and recommendations around data technology, data models, data storage and data analytics
Managing expectations of client service delivery.
Staying abreast of current business and industry trends relevant to the client's business
Effectively managing and motivating client engagement teams with diverse skills and backgrounds. Providing constructive on-the-job feedback/coaching to team members.
Fostering an innovative and inclusive team-oriented work environment. Playing an active role in counselling and mentoring junior consultants within the organization
Cultivating and managing business development opportunities. Developing and maintaining long-term client relationships and networks.
To qualify for the role you must have
Bachelor’s degree, or MS degree in Computer Science, Informatics, Statistics, Applied Mathematics, Data Science, or Machine Learning. Ph. D. preferred
At least three years hands-on experience with data science, AI, and big data. Experience with data engineering is a plus
Deep understanding of statistical and machine learning modeling with experience applying these modeling techniques to business problems
Machine learning using k-NN, naive bayes, decision trees, SVM experience required
Experience using data mining and statistical tools
Solid pattern recognition and predictive modelling skills
Knowledge of recommendation engines, scoring systems, A/B testing
Experience leveraging a variety of services to act as data sources such as Azure Data Lake, Azure Synapse Analytics, Azure SQL, Azure EventHub/IoT Hub, etc.
Hands-on experience with analytics and big data technologies within Microsoft Azure, with experiences in tools such as Azure Data Factory, Azure Machine Learning, Azure Cognitive Services, Azure Databricks and Azure Synapse Analytics.
Knowledge and experience with leveraging distributed techniques for training and scoring machine learning models, ideally using Azure Databricks
Knowledge and experience with one or more cloud available Machine Learning frameworks and tools such as Tensor Flow, PyTorch, ONNX, Weka, NumPy, PyMongo, etc.
Knowledge and experience with Model Management, ideally using Azure ML service and/or MLFlow as well as deployment of models using Azure Kubernetes Service
Knowledge of using automated machine learning (AutoML) frameworks to enhance productivity
Experience working in Python, R, Scala, and/or T-SQL
Extensive experience connecting to Data Platforms including data lakes, data warehouses, NoSQL databases, and APIs.
Ability to set up data and experimental platforms
Communication is essential, must be able to listen and understand the question and develop and deliver clear insights.
Outstanding team player.
Independent and able to manage and prioritize workload.
Ability to quickly and positively adapt to change.
A valid driver’s license in the US; willingness and ability to travel to meet client needs.
Ideally, you’ll also have
Bachelor’s Degree or above in mathematics, information systems, statistics, computer science, or related disciplines
Experience with ETL, ELT, data ingestion/cleansing and engineering skills
MS Certification: Azure Data Scientist Associate, Azure Fundamentals
Valid through: 10/29/2021
$100K — $150K *
$200K — $250K *
12 days ago