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About the role
As a Healthcare Data Science Manager, you will lead advanced analytics and data science initiatives within the healthcare domain. Your responsibilities will include: - Leading and managing a team of data scientists, analysts, and ML engineers. - Designing and implementing advanced analytics solutions including predictive modeling, machine learning, and AI-driven insights. - Working closely with stakeholders across healthcare operations, clinical teams, and business leadership to identify data-driven opportunities. - Developing models for patient risk stratification, readmission prediction, disease progression modeling, and revenue cycle optimization. - Ensuring compliance with healthcare data standards (HIPAA, HL7, FHIR, etc.). - Driving data governance, quality, and security practices. - Translating complex analytical findings into actionable business insights. - Overseeing the end-to-end data science lifecycle (data collection, preprocessing, modeling, validation, deployment). - Collaborating with engineering teams to deploy scalable data solutions. - Staying updated with emerging trends in healthcare analytics and AI. Qualifications required for this role include: - Bachelors or Masters degree in Data Science, Statistics, Computer Science, Healthcare Analytics, or related field (PhD preferred). - 10+ years of experience in data science, with at least 3-5 years in a leadership/managerial role. - Strong experience in the healthcare domain (payer, provider, pharma, or life sciences). - Expertise in Python / R, Machine Learning (Supervised & Unsupervised), Deep Learning (preferred), SQL & Big Data technologies (Spark, Hadoop). - Experience with healthcare datasets such as EMR/EHR, claims, or clinical data. - Strong understanding of statistical modeling and data mining techniques. Preferred skills for this role include: - Experience with cloud platforms (AWS, Azure, GCP). - Knowledge of NLP in healthcare (clinical text analysis). - Exposure to tools like Tableau, Power BI for visualization. - Experience with MLOps and model deployment pipelines. - Familiarity with regulatory compliance and data privacy laws. In addition to technical skills, leadership & soft skills are essential for this role: - Strong team management and mentoring skills. - Excellent communication and stakeholder management. - Strategic thinking and problem-solving mindset. - Ability to translate business problems into analytical solutions. Your key competencies should include: - Healthcare Domain Expertise - Advanced Analytics & Machine Learning - Leadership & Team Management - Data Strategy & Governance - Stakeholder Engagement As a Healthcare Data Science Manager, you will lead advanced analytics and data science initiatives within the healthcare domain. Your responsibilities will include: - Leading and managing a team of data scientists, analysts, and ML engineers. - Designing and implementing advanced analytics solutions including predictive modeling, machine learning, and AI-driven insights. - Working closely with stakeholders across healthcare operations, clinical teams, and business leadership to identify data-driven opportunities. - Developing models for patient risk stratification, readmission prediction, disease progression modeling, and revenue cycle optimization. - Ensuring compliance with healthcare data standards (HIPAA, HL7, FHIR, etc.). - Driving data governance, quality, and security practices. - Translating complex analytical findings into actionable business insights. - Overseeing the end-to-end data science lifecycle (data collection, preprocessing, modeling, validation, deployment). - Collaborating with engineering teams to deploy scalable data solutions. - Staying updated with emerging trends in healthcare analytics and AI. Qualifications required for this role include: - Bachelors or Masters degree in Data Science, Statistics, Computer Science, Healthcare Analytics, or related field (PhD preferred). - 10+ years of experience in data science, with at least 3-5 years in a leadership/managerial role. - Strong experience in the healthcare domain (payer, provider, pharma, or life sciences). - Expertise in Python / R, Machine Learning (Supervised & Unsupervised), Deep Learning (preferred), SQL & Big Data technologies (Spark, Hadoop). - Experience with healthcare datasets such as EMR/EHR, claims, or clinical data. - Strong understanding of statistical modeling and data mining techniques. Preferred skills for this role include: - Experience with cloud platforms (AWS, Azure, GCP). - Knowledge of NLP in healthcare (clinical text analysis). - Exposure to tools like Tableau, Power BI for visualization. - Experience with MLOps and model deployment pipelines. - Familiarity with regulatory compliance and data privacy laws. In addition to technical skills, leadership & soft skills are essential for this role: - Strong team management and mentoring skills. - Excellent communication and stakeholder management. - Strat