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Strong employer brand and metro location increase competition, though specialized ML/MLOps skills moderate applicant density.
Role's deep ML/AI, MLOps, and healthcare analytics emphasis limits cross-industry transferability.
Explicit 7+ years and mandatory production ML, generative AI, and MLOps requirements make shortlisting stringent.
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Lead end-to-end development and deployment of advanced analytics, machine learning, generative AI, and AI products for the Commercial domain.
Translate business objectives into AI solutions that drive measurable impact and embed these into business processes.
Mentor technical teams and establish standards for AI solution quality, scalability, performance, and responsible AI practices.
Minimum 7+ years of experience in data science, advanced analytics, AI, or machine learning.
Bachelor's degree in Engineering, Computer Science, Data Science, Statistics, Mathematics, Analytics, or related quantitative field.
Strong technical skills in Python, SQL, statistical modeling, machine learning frameworks (Scikit-Learn, TensorFlow, PyTorch, XGBoost), and MLOps practices.
Experience developing and deploying production-grade AI/ML solutions including generative AI and cloud analytics platforms like Snowflake.
Experienced in translating complex business needs into scalable AI products with operational ownership through full lifecycle management.
Proficient with modern AI/ML engineering practices including CI/CD, testing, pipeline automation, and enterprise API development.
Comfortable working in global cross-functional teams with strong stakeholder engagement and technical leadership abilities.