Senior AI Scientist

Ochsner Health•New Orleans, LA

About The Position

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.

Requirements

Bachelor's Degree in Data Science, Computer Science, Mathematics, Statistics, Economics, or other related field.
5 years Data science or Analytics in Healthcare

Nice To Haves

Master's Degree in Data Science, Computer Science, Mathematics, Statistics, Economics, or other related field.
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 toleadership.
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.
Exceptional verbal and written communication skills, with the ability to translate complex data science concepts into strategic business initiatives and influence stakeholders.
Strong interpersonal skills with demonstrated leadership and mentorship capabilities.
Expertise in advanced analytical techniques, problem-solving, and model evaluation, in addition to strong story-telling and trobleshooting skills.
Advanced proficiency in programming languages such as Python and SQL, as well as expertise in specialized machine learning frameworks including but not limited to TensorFlow or PyTorch.
Ability to communicate and present technical concepts to executive-level and cross-departmental audiences, including creating dashboards to aid in explaining analytics.
Expertise in leading-edge data visualization tools and techniques, in addition to a strong understanding of charts, dashboards, and reporting tools.
Exceptional attention to detal.
Ability to lead and influence key business initiatives through positive relationships, effective communication, and cross-team colloboration.

Responsibilities

Leads and strategically directs the design, deployment, and evaluation of computational algorithms and predictive models across multiple business units, while overseeing junior data scientists on these projects.
Researches and implements cutting-edge maching learning techniques and statistical tests to drive innovation in healthcare analytics by staying updated with current academic and industry trends.
Establishes best practices for team in data science and software development, including version control, testing, and containerization, ensuring deployable models and repeatable analyses across teams.
Develops internal training programs and guidelines as the quantitative subject matter expert (SME), providing mentorship to junior data scientists and guiding the team in project/program design, statistical methodology, and model interpretation.
Aligns data science goals with business objective, working directly with business partners in project scoping, timeline management, and documentation.
Influences organizational strategies through regular engagement, communication, and high-level presentations to both internal and external stakeholders.
Authors technical reports, statistical analysis plans (SAP), white papers, and peer-reviewed publications as needed.
Oversees the entire data pipeline, from acquisition to analytics, ensuring data quality and governance standards, and guiding junior team members in these processes.
Performs other related duties as assigned.
Remains knowledgeable on current federal, state and local laws, accreditation standards or regulatory agency requirements that apply to the assigned area of responsibility and ensures compliance with all such laws, regulations and standards.
This 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.