
Principal Data Science Architect
2 weeks ago
You must have deep technical experience working with technologies related to artificial intelligence, machine learning and deep learning. A strong mathematics and statistics background is preferred, in addition to experience building complex classification/extraction models extracting data from documents i.e. form, unstructured documents and IDs.
Key responsibilities include understanding the workflow and pipeline architectures of ML and deep learning workloads, designing AI architecture and pipeline planning, as well as leveraging knowledge of advanced analytics tools (such as Python) along with applied mathematics, ML and Deep Learning frameworks (such as PyTorch, Tensorflow).
Required Skills and Qualifications:- AI/ML Pipeline Planning: Design and implement end-to-end AI/ML pipelines for large-scale data processing and analysis.
- Data Science and Advanced Analytics: Develop and apply advanced statistical and mathematical models to solve complex business problems.
- AWS AI Services: Hands-on experience building, training, and deploying machine learning models on AWS infrastructure.
- MLOps Principles: Exposure to practices and processes for managing the lifecycle of machine learning models, including model development, deployment, monitoring, and maintenance.
Additional qualifications include wealth / insurance domain knowledge, thought leadership, and a collaborative mindset.
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