Senior AI Scientists

We've made a lot of progress since opening the doors in 1942, but one thing has never changed - our commitment to serve, heal, lead, educate, and innovate. We believe that every award earned, every record broken and every patient helped is because of the dedicated employees who fill our hallways. At Ochsner, whether you work with patients every day or support those who do, you are making a difference and that matters. Come make a difference at Ochsner Health and discover your future today! 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. To perform this job successfully, an individual must be able to perform each essential duty satisfactorily. The requirements listed below are representative of the knowledge, skill, and/or ability required. Reasonable accommodations may be made to enable qualified individuals with disabilities to perform the essential duties. This job description is a summary of the primary duties and responsibilities of the job and position. It is not intended to be a comprehensive or all‑inclusive listing of duties and responsibilities. Contents are subject to change at the company's discretion. 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 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. Ensure 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 trade‑offs 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 platforms, GenAI capabilities, safety frameworks, and healthcare analytics, rapidly prototyping promising technologies and formalizing them into Ochsner standards. Remote work is allowed but must report to an Ochsner office in New Orleans or Baton Rouge 1–2 days per week. Other Requirements Epic certifications, including: Clarity Data Model, Clinical Data Model, Cogito, Cosmos for Data Scientist, and Cosmos Data Model for Data Architect. Advanced ability to design, architect, and explain artificial intelligence (AI) solutions, including machine learning and generative AI systems, to both technical team members and non‑technical stakeholders such as clinicians, operational leaders, and executives. At least five (5) years of professional experience programming in Python, R, and/or SQL, including development of data pipelines, advanced analytics, predictive modeling, and AI‑based decision support solutions. Senior‑level experience developing, evaluating, and operationalizing machine learning and generative AI (LLM‑based) applications, including selecting appropriate modeling approaches, tuning performance, and assessing real‑world impact. Experience using enterprise analytics and AI platforms, specifically Snowflake and Snowflake Cortex to perform large‑scale data processing, feature engineering, vector search, and model or AI application deployment. Experience deploying and supporting AI or machine learning models within Epic Nebula ensuring integration with clinical workflows and operational systems. Experience establishing or following advanced AI development and operations practices, including model and prompt versioning, monitoring of performance and drift, documentation (e.g., model cards), and controlled deployment into production systems. Strong foundation in applied statistics and advanced analytics, including regression analysis, hypothesis testing, experimental or observational study design, and interpretation of results for decision making. Experience working with large‑scale enterprise datasets, such as electronic health records (EHRs), clinical systems, or operational databases, and converting raw data into structured analytics datasets suitable for AI modeling. Knowledge of data governance, security, and privacy standards, particularly in regulated environments such as healthcare, including compliance with HIPAA and protection of sensitive patient data. Ability to provide technical leadership in AI initiatives, including advising on AI strategy, evaluating emerging AI technologies, and guiding adoption of advanced AI capabilities across business or clinical domains. Five years of experience must be in progressively responsible work. Applicants must reference REQ_00268032 and apply online at Physical and Environmental Demands The physical demands described here are representative of those that must be met by an employee to successfully perform the essential functions of this job. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions. Sedentary work – Exerting up to 10 pounds of force occasionally and/or a negligible amount of force frequently to lift, carry, push, pull, or otherwise move objects. Jobs are sedentary if walking and standing are required only occasionally, and all other sedentary criteria are met. Normal routine involves no exposure to blood, body fluid or tissue and, as part of their employment, incumbents are not called upon to perform or assist in emergency care or first aid. The incumbent has no occupational risk for exposure to communicable diseases. Because the incumbent works within a healthcare setting, there may be occupational risk for exposure to hazardous medications or hazardous waste within the environment through receipt, transport, storage, preparation, dispensing, administration, cleaning and/or disposal of contaminated waste. The risk level of exposure may increase depending on the essential job duties of the role. Equal Opportunity Employer The employer maintains and complies with its Compliance & Privacy Program and Standards of Conduct, including the immediate reporting of any known or suspected unethical or questionable behaviors or conduct; patient/employee safety, patient privacy, and/or other compliance‑related concerns. The employer is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, or disability status. #J-18808-Ljbffr Koitecc Solutions