Data Scientist

Responsibilities:

• Analyse and model healthcare data to understand clinical patterns, patient journeys, and care delivery workflows across structured and unstructured datasets.
• Build data-driven AI agents that leverage clinical knowledge, patient data, and evidence-based decision making.
• Design pipelines for clinical data, including lab results, vital signs, metadata, and clinical notes.
• Create knowledge-grounded agent capabilities that combine clinical guidelines, medical literature, and real-world evidence.
• Implement evaluation frameworks for healthcare AI models with a focus on clinical accuracy, fairness, and safety metrics.

Requirements:

• Strong programming skills in Python (preferred), Go for building healthcare agents with experience in data science libraries (pandas, numpy, scikit-learn, etc)
• Healthcare domain knowledge with understanding of clinical workflows, medical terminology, and healthcare data standards is a plus.
• Experience with machine learning & NLP concepts applied to healthcare data, including time-series, and natural language processing of clinical text.
• Familiarity with clinical data sources such as EHR systems, claims data, lab results, and medical imaging.
• Experience with MLOps tools and model deployment pipelines for production applications.
• Mandatory Skills: Python, Pandas, Numpy, scikit-learn, NLP, Machine Learning, Artificial Intelligence, AI/ML, EHR systems, claims data, lab results, clinical workflows and Medical imaging.