Principle Data Scientist/Artificial Intelligence Engineer

at  Capgemini

WE ARE LOOKING FOR TALENTED AND MOTIVATED INDIVIDUALS WITH MANY BUT NOT NECESSARILY ALL THE FOLLOWING SKILLS AND EXPERIENCE:

• Experience of successfully large-scale delivery of AI techniques (e.g. supervised and un-supervised machine learning techniques, GenAI, deep learning, graph data analytics, statistical analysis, time series, geospatial, NLP, sentiment analysis, pattern detection, etc.).
• Strong communication skills - able to compellingly present work to clients, disseminating complex information in an easy-to-understand form on a day-to-day basis, and managing multiple stakeholder relationships and inspiring team-mates.Strong track record of building and leading technical teams, managing workloads and offering technical guidance and leadership, defining upskilling strategies, running Agile processes and identifying and mitigating project risks.
• Proven experience of winning work with private and public sector clients or internal clients within large organisations, through e.g. the RFI/RFP process, as preferred bidder, documented bids and face to face presentations and experience of data science platforms (e.g. Databricks, Dataiku, AzureML, SageMaker) and machine learning frameworks (e.g. Keras, Tensorflow, PyTorch, scikit-learn).
• Cloud platforms – demonstrable experience of leading teams who build and deploy solutions to Cloud (e.g. AWS, Azure, Google Cloud) including Cloud provisioning tools (e.g. Terraform).
• Technology deployment– demonstrable experience of leading teams using technologies such as Docker, Kubernetes, CI/CD platforms (e.g. Jenkins, Tekton, ArgoCD), GitHub, to deploy complex solutions robustly and securely.

Please refer the Job description for details