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Tier-1 employer, metro location, mid-level ML role and broad visibility drive high competition.
Healthcare domain, compliance and governance emphasis reduces cross-industry transferability.
Multiple mandatory skills, graduate pedigree, and 5+ years consultancy requirement enforce high shortlisting strictness.
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Design, develop, and deploy end-to-end AI/ML solutions including Generative AI for high-impact healthcare business challenges.
Translate business problems into validated models, ensuring data quality, governance, and compliance throughout model lifecycle.
Provide technical leadership and mentorship, promoting best practices in MLOps, model evaluation, and operational robustness.
Master's degree in Data Science, Computer Science, Statistics, Mathematics, or related field from a top university.
5+ years consultancy experience in data science, machine learning, or AI, preferably from MBB or Big 4 firms.
Strong programming skills in Python with experience in data science libraries, deep learning frameworks, and GenAI toolkits.
Practical experience with MLOps including CI/CD, model registries, experiment tracking, and cloud deployment (AWS, Azure).
Experienced in delivering production AI/ML solutions end-to-end in complex, regulated environments such as healthcare.
Technically strong with both software engineering and advanced machine learning skills, including distributed computing frameworks and cloud-native ML platforms.
Proven ability to lead cross-functional teams and mentor peers, with a focus on operational quality, reproducibility, and ethical AI practices.