Lead Data Scientist

Job Title: Lead Data Scientist – Healthcare (AI Architecture Focus)Location: EAST coastKey Responsibilities• Lead the design, development, and deployment of advanced data science andmachine learning solutions within the healthcare domain.• Act as a technical lead, guiding data scientists and collaborating with AIArchitects to ensure scalable, secure, and compliant AI systems.• Architect and optimize end-to-end ML pipelines, including data ingestion,feature engineering, model training, validation, and deployment.• Work with structured and unstructured healthcare data such as EHR/EMR,claims, clinical notes, imaging metadata, and operational data.• Partner with stakeholders to define problem statements, success metrics, anddata strategies aligned with clinical and business goals.• Ensure models comply with healthcare regulations and standards, includingHIPAA and data privacy best practices.• Evaluate and recommend tools, frameworks, and cloud-based solutions for MLand AI workloads.• Oversee model monitoring, performance tuning, explainability, and governancein production environments.• Contribute to AI strategy, solution roadmaps, and architectural decisionsalongside AI and platform teams.Required Qualifications• 7+ years of experience in data science, with recent experience in a Lead DataScientist or similar senior role.• Strong experience working in the healthcare domain (payer, provider, lifesciences, digital health, or health tech).• Hands-on experience designing and deploying ML models in productionenvironments.• Solid understanding of AI architecture concepts, including scalable MLsystems, MLOps, and cloud-based deployments.• Proficiency in Python and common ML libraries (e.g., scikit-learn, TensorFlow,PyTorch).• Experience with SQL and big data technologies (e.g., Spark, Databricks,Snowflake).• Strong understanding of data modeling, statistics, and machine learningalgorithms.• Experience working in cloud environments such as AWS, Azure, or GCP.• Excellent communication skills with the ability to explain complex technicalconcepts to non-technical stakeholders.Preferred Qualifications• Prior experience collaborating closely with or acting as an AI Architect onenterprise-scale solutions.• Experience with MLOps tools and frameworks (e.g., MLflow, Kubeflow,SageMaker, Azure ML).• Familiarity with NLP, computer vision, or generative AI use cases in healthcare.• Knowledge of healthcare interoperability standards such as HL7, FHIR, or ICDcodes.• Experience leading cross-functional teams in a contract or consultingenvironment.