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Tier-1 brand increases competition, but senior, specialized ML focus reduces generalist applicant density.
Advanced ML skills transfer across industries, but healthcare revenue-cycle preference adds domain specificity.
Explicit 8+ years requirement and mandatory advanced ML and production deployment skills create rigorous filters.
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Lead development of advanced ML and statistical models addressing complex healthcare problems, ensuring scalable data science solutions.
Establish and promote best practices in modeling, experimentation, and analytical rigor within the team.
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 fields such as Computer Science, Statistics, or Mathematics.
Bachelor of Engineering degree mandatory.
Proven experience with statistical modeling, machine learning, large datasets, and deployment of models to production.
Prior healthcare domain experience or knowledge, particularly in healthcare revenue cycle, preferred but not mandatory.
Experienced in advanced ML methods including Transformers, deep learning frameworks, and graph-based ML techniques.
Able to independently manage ambiguous problems and deliver impactful outcomes with strong collaboration and communication skills.
Familiarity or interest in causal inference and decision-focused modeling with ability to work effectively with global stakeholders.