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Medium competition from Bangalore location and in-demand GenAI/ML skills despite senior/principal level.
Medium because core ML skills transfer, though healthcare domain experience is preferred for product context.
High due to explicit 7+ years, Principal-level, and mandatory production GenAI, MLOps, and cloud experience.
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Design, develop, and operationalize reusable data analytics and AI/ML products on the digital health data platform.
Collaborate cross-functionally with product managers, data engineers, and business stakeholders to build advanced ML models that drive actionable insights and support critical business decisions.
Coach and mentor junior data scientists, and establish architecture, engineering standards, and governance for analytics solutions across teams.
Bachelor's degree or higher in quantitative disciplines such as Statistics, Data Science, Computer Science, or Engineering.
7+ years experience in advanced analytics and ML model development for complex business problems.
3+ years experience in MLOps including end-to-end development and deployment of analytics products.
3+ years building cloud analytics solutions on AWS, Azure, or GCP; proficient in Python and SQL; hands-on experience with GenAI application development and ownership of production GenAI or agentic-AI systems.
Experienced Principal-level data scientist with strategic and operational ownership of AI/ML architectures and productization in digital health or related domains.
Comfortable working in agile, cross-functional teams, balancing technical leadership and collaboration with business stakeholders.
Demonstrates deep expertise in ML/deep learning theory, practical GenAI applications, and cloud-based AI product development aligned with healthcare analytics.