Data Scientist

Key Skills

Aartificial intelligence, Ansible, Azure, Data science techniques, Docker, Effective communication skills, Jenkins, Machine learning techniques, MLflow, Python Programming, SQL

Job Description

• Supporting the Market teams in building go to market strategies
• 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
• Play a key role in the end-to-end delivery of AI solutions for our clients, from ideation, feasibility assessment, to data preparation, modelling and industrialization
• Research & development in support of new AI based offerings
• Developing & delivering client solutions using a range of DS/AI technologies
• 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
• Supporting delivery of AI strategy engagements (eg AI benchmarking studies, AI training engagements, AI governance projects)
• Supporting delivery of trustworthy and responsible AI engagements (embedding trust, and harnessing the value of AI and data science in an ethical and responsible manner)
• Learning about new technologies/research and how they could be applied for the benefit of our clients
• Mentoring and managing other experienced and aspiring Data Science & AI Engineers
• Managing bid response work to articulate what value we can bring
• Collaborating with our partners and other parts of EY
• Supporting thought leadership creation, demonstrations and other materials that articulate our point of view on intelligent automation and AI to both clients and EY colleagues

To qualify for the role, you must have 

• MS degree in Computer Science, Informatics, Statistics, Applied Mathematics, Data Science, or Machine Learning. Ph. D. preferred
• Minimum of 5 years of hands-on experience with data science, AI, and big data. Experience with data engineering is a plus
• Extensive hands on experience in delivering Data Science models (Demand Forecasting, Time series forecasting, ML etc.)
• Good understanding of statistical and machine learning modeling with experience applying these modeling techniques to business problems
• Knowledge of using automated machine learning (AutoML) frameworks to enhance productivity
• Experience working in Python and SQL
• Ability to deliver work independently as well as with a team
• Strong written and verbal communication in English, presentation, client service and technical writing skills for both technical and business audiences

Skills & Attributes for Success

If you have some or all of the below, then get in touch:

• Strong client facing sales pursuit and delivery skills
• Professional experience in delivery of advanced analytics/DS/AI projects
• Excellent understanding of mathematical, probability & statistics principles, and of algorithm theory 
• Detailed knowledge of a range of AI techniques including, graph data analytics, time series, NLP, deep learning, supervised and unsupervised machine learning etc
• Worked with open source data science libraries and understand how to apply them to various problem types
• Experience in handling unstructured data and structured data with large, complex and multiple data sets from various sources
• Experience of using the latest Data science platforms (e.g. Databricks, AzureML) and frameworks (e.g. Tensorflow, MXNet, scikit-learn)
• Knowledge and experience with Model Management, ideally using Azure ML service and/or MLFlow as well as deployment of models using Azure Kubernetes Service
• Data wrangling and manipulation techniques
• Experience of development & deployment tooling, such as Jenkins, Ansible, Docker etc
• Fluency in English