Senior AI & Data Scientist

Job Description

Join our team as a Senior AI & Data Scientist and lead the development of groundbreaking AI/ML solutions for healthcare's most pressing challenges. You'll design and deploy production-ready machine learning systems for critical applications like risk assessment, clinical decision-making, automated chart reviews, and fraud detection. Define technical strategies, select models, and create system architectures for multi-model systems and real-time decision engines processing millions of healthcare transactions. Responsibilities: * Architect complete AI/ML solutions for complex healthcare issues. * Design and implement production-grade machine learning systems for high-impact applications. * Manage the entire ML lifecycle from experimentation to production. * Build robust, scalable AI services for experimentation, validation, deployment, monitoring, and continuous improvement. * Establish instrumentation, observability, alerting, and feedback loops to ensure model performance. * Drive technical innovation and excellence. * Research and implement state-of-the-art methods in deep learning, NLP/LLMs, computer vision, and causal inference. * Champion engineering best practices for code quality, testing, and documentation. * Partner with cross-functional leaders and translate technical concepts into business narratives. * Provide technical mentorship and improve analytical rigor.

Qualifications

1. 5-8 years of experience delivering production-grade data science or ML solutions with demonstrable business impact. 2. Proven expertise in architecting complex ML systems from research to production deployment. 3. Deep knowledge in multiple ML domains and strong software engineering fundamentals. 4. Experience leading technical projects and mentoring data scientists. 5. Healthcare domain expertise, especially in Medicare Advantage, risk adjustment, or claims analytics (preferred). 6. Experience with production document understanding systems (OCR, NER, entity extraction, LLM pipelines) (preferred). 7. Published research, open-source contributions, or patents in ML/AI (preferred). 8. Track record of translating research innovations into production systems (preferred). 9. A Ph.D. in Computer Science, Machine Learning, Statistics, or a related field is required. 10. Commitment to continuous learning in ML/AI advancements, healthcare analytics, and software engineering practices (training required). 11. Training or certification in MLOps, cloud platforms (Azure, AWS, GCP), or healthcare regulations (HIPAA, CMS) (preferred). 12. Expert-level proficiency in Data Science methods, workflows, and best practices. 13. Advanced Machine Learning knowledge, including ensemble methods, deep learning, NLP, LLMs, and computer vision. 14. Strong Statistical Analysis and experimental design capabilities. 15. Expert programming skills in Python, Java, SQL, or PySpark with a focus on production-grade, maintainable code. 16. Proficiency with Databricks (Spark, Delta Lake), MLflow, Unity Catalog, and cloud platforms. 17. Experience with Git workflows, CI/CD pipelines, Docker, and modern MLOps practices. 18. Deep understanding of healthcare data (claims, clinical, member) and Medicare Advantage operations. 19. Exceptional communication skills: able to translate technical complexity into business value. 20. Strong data visualization and storytelling capabilities with a proven ability to influence technical decisions. 21. Experience with NoSQL databases, performance optimization, and distributed computing (preferred). 22. Real-time ML inference and streaming architectures (preferred). 23. Contributions to internal ML platforms, frameworks, or open-source projects (preferred). 24. Experience presenting at technical conferences or publishing research (preferred).