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Tier-1 brand and metro posting but senior, niche ML healthcare focus reduces candidate density.
Advanced ML skills transfer across industries, but healthcare domain preference raises sensitivity moderately.
Explicit 8+ years requirement plus specialized ML and production deployment experience makes shortlisting highly strict.
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Lead development of advanced machine learning and statistical models to solve complex healthcare problems, focusing on healthcare revenue cycle.
Establish best practices in modeling, experimentation, and analytical rigor; convert 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 a related quantitative field (Computer Science, Statistics, Mathematics).
Bachelor of Engineering degree required.
Experience with advanced machine learning methods including Transformers (NLP), deep learning frameworks, and graph neural networks.
Prior experience or domain knowledge in healthcare, particularly healthcare revenue cycle, preferred but not mandatory.
Experienced in handling large, high-dimensional datasets and delivering actionable insights in healthcare analytics.
Proficient in deploying ML models to production and familiar with modern ML techniques and healthcare domain challenges.
Able to work independently on ambiguous problems and influence global stakeholders through collaboration and communication.