Lead AI Architect & Principal Data Scientist (Healthcare & Life Sciences)

**Lead AI Architect & Principal Data Scientist (Healthcare & Life Sciences)** Location: Multiple Locations (Onsite/Hybrid/Remote) Duration: Full Time Salary: Excellent We are looking for a visionary **Data Scientist AI Architect** to lead the design, development, and deployment of enterprise-grade AI/ML systems tailored for healthcare. In this role, you will bridge the gap between advanced data science research and clinical-grade production systems, shaping our technical roadmap across diagnostics, predictive analytics, and clinical workflow optimization. **Key Responsibilities** - **Architecture & Strategy:** Define the overarching technical blueprint for healthcare AI/ML platforms, ensuring high availability, scalability, and seamless integration with EHR/EMR systems (Epic, Cerner) and imaging networks (PACS/DICOM). - **Model Innovation & Development:** Architect and guide the deployment of specialized ML, Deep Learning, and generative AI models (NLP/LLMs for clinical text, computer vision for medical imaging, risk-stratification models). - **Data Governance & Compliance:** Embed regulatory and privacy frameworks into system architecture by design—enforcing strict compliance with HIPAA, HITECH, FDA guidelines for SaMD (Software as a Medical Device), and GDPR. - **MLOps & Pipeline Engineering:** Lead the transition from proof-of-concept to robust CI/CD and MLOps pipelines handling multimodal health data, bias detection, drift monitoring, and explainable AI (XAI). - **Cross-Functional Leadership:** Partner closely with clinicians, bioinformatics researchers, data engineers, and product leadership to translate complex medical requirements into technical solutions. **Qualifications & Experience** - **Healthcare Domain Expertise:** 5+ years of direct experience working with healthcare data modalities (EHR, claims, clinical trials, or biomedical imaging) and standards (FHIR, HL7, DICOM, SNOMED CT, ICD-10). **Technical Mastery:** - Deep proficiency in Python, R, and frameworks like PyTorch, TensorFlow, and Hugging Face. - Hands-on expertise architecting end-to-end distributed pipelines on AWS (HealthLake, SageMaker), GCP (Healthcare API, Vertex AI), or Azure Health Data Services. - Strong foundation in statistical modeling, causal inference, and ethical AI/bias mitigation. - **Systems Architecture:** Demonstrated track record of deploying mission-critical machine learning systems into clinical or regulated environments. - **Education:** Master’s or Ph.D. in Computer Science, Biomedical Informatics, Data Science, Electrical Engineering, or a related quantitative discipline (or equivalent practical experience). **Why Join Us?** - Build technology that directly impacts patient care, clinician efficiency, and health equity. - Lead a high-caliber team of researchers, clinicians, and software engineers. - Competitive compensation, equity, and comprehensive health and wellness benefits.