Lead AI Architect & Principal Data Scientist (Healthcare & Life Sciences)
Celebal Technologies
India
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.