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Tier-1 brand and metro location increase competition, but seniority and niche ML/healthcare skills reduce applicant density.
Advanced ML techniques are transferable, but healthcare domain and leadership expectation raise industry specificity.
Explicit 8+ years, mandatory advanced ML techniques and production deployment experience create strict shortlisting filters.
Lead development of advanced ML and statistical models to address complex healthcare problems.
Establish best practices for modeling, experimentation, and analytics rigor, and mentor data science team members.
Collaborate with global stakeholders to influence product and business strategy and convert healthcare challenges into scalable data science solutions.
Minimum 8+ years of experience in data science or related quantitative fields (e.g., Computer Science, Statistics, Mathematics).
Bachelor of Engineering degree mandatory.
Proven expertise in machine learning, statistical modeling, and handling large high-dimensional datasets.
Experience deploying models in production; healthcare domain experience preferred but not strictly mandatory.
Experienced in modern ML methods including Transformers (NLP), deep learning frameworks, and graph-based machine learning.
Strong problem solver comfortable addressing ambiguous issues with impact-driven outcomes, especially in healthcare analytics.
Skilled at collaborating with diverse global stakeholders and mentoring technical teams.