Lead Data Scientist

We are looking for a Lead Data Scientist to own our core AI platform architecture and data formulation strategy. You will lead training data design, multimodal AI systems, and high-cardinality data mining across real-world healthcare datasets.

Responsibilities:

• Data Strategy and Mining: Structure, label, and mine historical decision data, claim outcomes, and domain signals to optimize continuous model performance.
• Platform Architecture: Own the architecture of batch, real-time inference, and model training pipelines across NLP, traditional ML, and Gen AI workloads.
• Multi-Modal Systems: Architect AI systems combining unstructured clinical text, structured EHR data, and domain knowledge.
• Engineering Leadership: Mentor AI engineers, lead technical build vs. buy evaluations, and drive engineering best practices.

Requirements:

• 8+ years building and deploying production AI/ML systems at scale.
• Technical Mastery: Deep experience in PyTorch/TensorFlow, NLP, traditional ML, and Gen AI deployments.
• Data Focus: Proven track record where data quality, active labeling strategy, and feature curation were the core drivers of success.
• Cloud and Infrastructure: Hands-on experience with AWS/Azure/GCP and containerized deployments (Docker, Kubernetes).

Preferred Experience:

• Building self-improving AI (RLHF, active learning, feedback loops).
• Healthcare domain exposure (FHIR, HL7 ICD, CPT) or regulated AI environments.
• MLOps tooling, multi-modal architectures, and interpretable/explainable AI systems.