SENIOR ENGINEERING MANAGER - NLP

We are seeking an experienced Healthcare Data Science Manager to lead advanced analytics and data science initiatives within the healthcare domain. The ideal candidate will combine strong technical expertise with domain knowledge in healthcare, driving data-driven decision-making, predictive modeling, and innovation across clinical, operational, and financial areas.
Key Responsibilities
Lead and manage a team of data scientists, analysts, and ML engineers.
Design and implement advanced analytics solutions including predictive modeling, machine learning, and AI-driven insights.
Work closely with stakeholders across healthcare operations, clinical teams, and business leadership to identify data-driven opportunities.
Develop models for:
Patient risk stratification
Readmission prediction
Disease progression modeling
Revenue cycle optimization
Ensure compliance with healthcare data standards (HIPAA, HL7, FHIR, etc.).
Drive data governance, quality, and security practices.
Translate complex analytical findings into actionable business insights.
Oversee end-to-end data science lifecycle (data collection, preprocessing, modeling, validation, deployment).
Collaborate with engineering teams to deploy scalable data solutions.
Stay updated with emerging trends in healthcare analytics and AI.
Required Qualifications
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 35 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
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.

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