Senior AI Scientist

Exceptional care starts with exceptional people.

For us, this is more than a job– it’s a calling. It’s waking up each day, looking for ways to make a difference with a compassionate, inclusive and talented team. Ochsner empowers you to discover your passion, reach your potential, and Pursue Your Purpose. Exceptional care starts with exceptional people and teams. Together we are leading the way.

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 algorthims 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.

Education Required
- Bachelor's Degree in Data Science, Computer Science, Mathematics, Statistics, Economics, or other related field.

Preferred
- Master's Degree in Data Science, Computer Science, Mathematics, Statistics, Economics, or other related field.

Work Experience Required
-5 years Data science or Analytics in Healthcare

Preferred Qualifications Five or more years of professional experience in data science, applied machine learning, artificial intelligence, advanced analytics, healthcare analytics, or a related quantitative or technical role.

Demonstrated hands-on experience developing, evaluating, deploying, monitoring, or supporting production AI or machine-learning solutions.

Experience evaluating generative AI, large language model, or conversational AI systems using methods such as evaluation frameworks, scenario-based testing, automated or human review, prompt experimentation, and controlled testing of model or configuration changes.

Strong proficiency in Python and SQL, including experience developing data pipelines, advanced analytics, machine-learning models, or AI-based solutions.

Strong foundation in statistical modeling and experimental design, including the ability to establish performance metrics, analyze results, and determine whether changes produce meaningful improvements.

Experience working with large-scale datasets and cloud-based AI or machine-learning platforms, with familiarity with modern development, deployment, MLOps, or LLMOps practices.

Ability to assess complex technical systems, diagnose performance issues, and translate findings into practical and measurable improvements.

Strong written and verbal communication skills, including the ability to collaborate acrosstechnical and operational teams and explain findings, risks, and recommendations to leadership.

Additional

Preferred Qualifications Hands-on experience with voice agents, conversational AI, natural language processing, agentic AI, or other generative AI applications.

Experience supporting conversational AI across development, evaluation, deployment, production monitoring, and continuous improvement.

Experience with AI evaluation approaches such as rubric-based scoring, human evaluation, LLM-as-judge, A/B testing, canary releases, or similar methodologies.

Experience analyzing voice-agent performance, including transcripts, audio signals, intent recognition, task completion, escalation, transcription quality, and latency.

Experience with prompt development, retrieval-augmented generation, tool use, knowledge sources, and conversational workflows.

Experience working in healthcare or another regulated environment, including familiarity with responsible AI, privacy, security, and the handling of PHI, PII, or other sensitive information.

Experience with R or another statistical programming language.

Experience providing technical leadership or mentoring technical professionals.

Knowledge

Skills and Abilities

(KSAs)
Exceptional verbal and written communication skills, with the ability to translate complex data science concepts into strategic business…