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Strong Tier-1 brand but senior, specialized ML healthcare role reduces generalist applicant density.
Highly technical ML skills transferable, but healthcare revenue-cycle domain knowledge increases specialization.
Explicit 8+ years requirement plus advanced ML, production deployment and domain expectations.
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Lead the development and deployment of advanced machine learning and statistical models focused on solving complex healthcare problems, especially in healthcare revenue cycle.
Establish and promote best practices in modeling, experimentation, and analytical rigor while converting healthcare challenges into scalable data science solutions.
Collaborate with global stakeholders to influence product and business strategy and mentor the data science team to enhance technical capabilities.
8+ years of experience in data science or related quantitative field (e.g., Computer Science, Statistics, Mathematics).
Bachelor of Engineering degree mandatory.
Strong expertise in statistical modeling, machine learning, and handling large high-dimensional datasets.
Experience with advanced ML methods including transformers (NLP), deep learning frameworks, and graph-based machine learning.
Experienced in healthcare data science with domain knowledge of healthcare revenue cycle.
Able to independently handle ambiguous problems and derive impactful data-driven outcomes.
Skilled in collaborating with diverse global stakeholders and mentoring junior team members in a technical capacity.