Senior AI Scientists

Sr Data Scientist

This senior-level role is pivotal in driving healthcare innovation through cutting-edge data science and machine learning technologies. The Sr Data Scientist not only develops advanced algorithms but also plays a key role in strategic decision-making processes. This individual will lead projects that optimize healthcare outcomes and improve financial efficiency and will act as a mentor and technical leader within the data science team.

Job Duties:

AI Strategy, Portfolio Leadership, and Enterprise Direction:
Define and evolve Ochsner's artificial intelligence and machine learning (AI/ML) strategy across predictive analytics, generative AI (GenAI/LLMs), Snowflake Cortex capabilities, and Epic ecosystem integration to advance clinical, operational, and financial outcomes. Partner with senior leadership to prioritize, fund, and align AI initiatives across business units and enterprise portfolios.

Architecture and Delivery of Enterprise AI, GenAI, and ML Solutions:
Lead the end to end architecture, development, validation, and deployment of advanced analytics solutions, including traditional ML models and advanced AI systems, e.g., large language model (LLM) applications, retrieval augmented generation, agent based systems, and AI driven decision support tools. Guide cross functional teams through complex technical challenges and delivery to produce production ready AI systems.

AI Platform Engineering Using Snowflake Cortex and Cloud Technologies:
Design and implement AI and analytics solutions using Snowflake Cortex and related cloud based technologies, including hosted LLMs, vector functions, feature engineering pipelines, Snowpark ML, secure user defined functions, and integrated deployment workflows. Establish best practices for scalability, governance, repeatability, and performance across predictive and GenAI workloads.

Clinical AI Deployment and Operationalization in Epic Ecosystems:
Lead the packaging, validation, deployment, monitoring, and lifecycle management of ML and AI solutions within Epic Nebula or comparable healthcare analytics environments. Ensures AI systems are integrated with clinical workflows, adhere to patient safety requirements, pass platform specific reviews, and meet HIPAA and PHI/PII standards.

MLOps, LLMOps, and Production Governance:
Establish and enforce standards for AI development and operations, including experiment tracking, model and prompt versioning, evaluation pipelines, CI/CD, vector storage, safety testing, and production observability. Monitor latency, drift, hallucination risk, and cost while aligning operational practices across Snowflake, Epic, and enterprise platforms.

Responsible AI, Compliance, and Data Governance:
Own enterprise AI governance practices, including data quality, lineage, metadata management, security controls, bias assessment, transparency requirements, human in the loop workflows, audit trails, model cards, prompt cards, incident response procedures, and regulatory documentation aligned with healthcare standards.

Technical Leadership, Mentorship, and AI Capability Building:
Serve as a subject matter expert in ML, advanced AI, GenAI/LLMs, Snowflake Cortex, Epic deployment, applied statistics, causal inference, and experiment design. Provide technical mentorship through design reviews, code reviews, training sessions, and AI upskilling initiatives, elevating Ochsner's AI maturity.

Cross Functional Collaboration and Executive Communication:
Work directly with clinical leadership, operations, engineering, data governance, information security, legal/compliance teams, Epic stakeholders, and project management offices to define value driven AI use cases, align workflows, manage timelines, and ensure successful enterprise adoption. Communicate AI strategy, performance, risks, and tradeoffs to executive leadership and Ochsner governance bodies.

Innovation, Continuous Improvement, and Industry Leadership:
Monitor production AI and ML systems using defined service level indicators and objectives, drive continuous improvement based on feedback, and iterate on models, prompts, and retrieval strategies. Scan emerging trends in AI…