Senior Group Technical Architect

Job Summary

• 11–14 years of experience in data science / AI-ML roles
• Strong Python skills; hands-on experience with ML/deep learning frameworks (e.g., PyTorch, TensorFlow, scikit-learn)
• Signal processing experience, ideally with biomedical or other time-series signals (ECG or similar)
• Solid grounding in statistics and mathematical formulation of models
• Experience with image processing and analysis is a plus
• Able to own a problem end-to-end — from data audit through to a production-ready model or report, not just isolated experimentation
• Experience working with healthcare data is required; specific experience with cardiopulmonary datasets is an added advantage
• Experience working in AWS cloud environments, using Jupyter notebooks for running model training, simulation, and hypothesis testing
• Understanding of data security and privacy practices when handling sensitive health data

Key Responsibilities

• 11–14 years of experience in data science / AI-ML roles
• Strong Python skills; hands-on experience with ML/deep learning frameworks (e.g., PyTorch, TensorFlow, scikit-learn)
• Signal processing experience, ideally with biomedical or other time-series signals (ECG or similar)
• Solid grounding in statistics and mathematical formulation of models
• Experience with image processing and analysis is a plus
• Able to own a problem end-to-end — from data audit through to a production-ready model or report, not just isolated experimentation
• Experience working with healthcare data is required; specific experience with cardiopulmonary datasets is an added advantage
• Experience working in AWS cloud environments, using Jupyter notebooks for running model training, simulation, and hypothesis testing
• Understanding of data security and privacy practices when handling sensitive health data

Skill Requirements

• 11–14 years of experience in data science / AI-ML roles
• Strong Python skills; hands-on experience with ML/deep learning frameworks (e.g., PyTorch, TensorFlow, scikit-learn)
• Signal processing experience, ideally with biomedical or other time-series signals (ECG or similar)
• Solid grounding in statistics and mathematical formulation of models
• Experience with image processing and analysis is a plus
• Able to own a problem end-to-end — from data audit through to a production-ready model or report, not just isolated experimentation
• Experience working with healthcare data is required; specific experience with cardiopulmonary datasets is an added advantage
• Experience working in AWS cloud environments, using Jupyter notebooks for running model training, simulation, and hypothesis testing
• Understanding of data security and privacy practices when handling sensitive health data

Other Requirements

• 11–14 years of experience in data science / AI-ML roles
• Strong Python skills; hands-on experience with ML/deep learning frameworks (e.g., PyTorch, TensorFlow, scikit-learn)
• Signal processing experience, ideally with biomedical or other time-series signals (ECG or similar)
• Solid grounding in statistics and mathematical formulation of models
• Experience with image processing and analysis is a plus
• Able to own a problem end-to-end — from data audit through to a production-ready model or report, not just isolated experimentation
• Experience working with healthcare data is required; specific experience with cardiopulmonary datasets is an added advantage
• Experience working in AWS cloud environments, using Jupyter notebooks for running model training, simulation, and hypothesis testing
• Understanding of data security and privacy practices when handling sensitive health data