Vice President, Applied AI and Data Science

Job Title: Vice President, Applied AI and Data Science

FLSA Classification: Exempt

Revision Date: 11/2026

Role Type: Remote or Hybrid (Jacksonville/Nashville)

About Mosai

Mosai™ is the intelligent care coordination platform that brings together the fragmented pieces of healthcare into a clear, connected picture. Like a mosaic, our platform unites data, people, and processes so providers can make better decisions, coordinate care in real time, and deliver improved outcomes. With Mosai, home-based care organizations can thrive in value-based care while giving every patient the right care, in the right place, at the right time. Learn more at​ https://www.mosai.com/

Position Summary

The Vice President, Applied AI and Data Science leads the design, delivery, and ongoing quality of the AI solutions at the core of Mosai's product suite. These include generative AI and large language models (LLMs), agentic workflows, and the machine learning and statistical models that complement them. This leader manages a team and is accountable for results that matter to customers: better clinical decisions, more efficient care coordination, and measurable improvements in patient outcomes and clinician productivity.

This role requires a technical AI leader with deep grounding in clinical intelligence and healthcare data & informatics. This role does not need to be a licensed clinician, but must understand clinical data, clinical workflows, and how care is delivered well enough to build AI that clinicians trust and use. The VP will ensure that every model and AI-enabled feature is clinically credible, evaluated, safe, and valuable to the providers and organizations who rely on it as a part of their work. This role will continually evaluate the needs and outcomes and select, leverage a suite of language models (commercial and open-source) against the needs of each use case, and will apply classical machine learning where it is the right tool. The VP must balance Mosai's entrepreneurial culture with the discipline required to deliver production-grade AI in a highly regulated environment.

Job Duties:

Leadership and Strategy

• Lead, mentor, and scale the Applied AI and Data Science organization.
• Set the vision, roadmap, and operating model for applied AI, aligned to Mosai's product strategy, customer needs, and value-based care objectives.
• Create a culture of innovation, experimentation, and accountability that encourages smart risk-taking on ambiguous problems while holding a high bar for quality.
• Serve as a trusted executive voice on AI, translating complex technical concepts into business value and customer impact for executives, clinical leaders, customers, and the board.

Customer Value and Outcomes

• Own delivery of AI and data science solutions (GenAI, machine learning, and statistical) powering Mosai's products, with clear linkage to customer outcomes such as avoidable utilization, care quality, patient risk stratification, workflow efficiency, and clinician experience.
• Partner with product and clinical stakeholders to define success metrics for each solution, track realized customer value after deployment (not just model performance), drive adoption, gather feedback, and prioritize improvements that increase value.
• Apply clinical intelligence and informatics expertise to ensure AI features fit real home-based & hospice care workflows and to support frontline clinicians.

AI Technology Strategy

• Drive the strategy for a suite of language models, including selecting, benchmarking, and routing across frontier commercial LLMs, open-source and fine-tuned models, and small language models (SLMs) and other specialized models based on accuracy, safety, cost, latency, and data privacy requirements, favoring SLMs where they deliver sufficient quality at lower cost and latency.
• Lead the adoption of modern GenAI techniques, with particular emphasis on designing, building, and managing agentic workflows, as well as retrieval-augmented generation (RAG), tool use, fine-tuning, prompt engineering, and structured extraction from clinical notes and other unstructured data.
• Drive the buildout and requirements for the MosaiAI platform, such as skill libraries, prompt repo, labeling studio, etc.
• Continue to apply classical machine learning (predictive modeling, risk stratification, time-series, causal inference) where it is the right tool, and apply sound judgment on when to use GenAI and when not to.
• Stay current on the rapidly evolving AI landscape, bringing in new methods, models, and tooling where they deliver measurable value, and leverage open-source technologies and scalable cloud infrastructure (AWS, Azure, or GCP) to accelerate delivery and control cost.

AI Quality and Evaluation

• Establish and enforce clear standards for model and AI development, validation, and release, including clinical validity, calibration, subgroup performance, bias and fairness assessment, and explainability.
• Build and maintain comprehensive evaluation frameworks for LLM, GenAI, and agentic workflow solutions, including benchmark and golden datasets, end-to-end testing of multi-step agent behavior and tool use, automated and clinician-in-the-loop evaluation, hallucination and factuality testing, safety and red-teaming, and regression testing across model and prompt changes.
• Implement production monitoring for drift, performance degradation, data quality, cost, and latency, with defined thresholds, alerting, and remediation processes.
• Ensure appropriate human oversight, guardrails, and transparency for AI-assisted clinical and operational decisions.

Governance, Compliance, and Responsible AI

• Establish and lead AI governance practices, including model documentation, versioning, approval processes, audit trails, and responsible AI principles, and ensure solutions comply with HIPAA and applicable healthcare privacy, security, and regulatory requirements, including considerations for clinical decision support and emerging AI regulation.
• Partner with Security, Compliance, Legal, and Clinical leadership to manage risk in the use of PHI, third-party model providers, and AI vendors.

Cross-Functional Partnership

• Partner with Product, Engineering, IT, Data Engineering, Clinical, and Customer teams to deliver reliable, scalable solutions and share ownership of customer adoption and growth objectives.
• Collaborate on data pipelines, MLOps/LLMOps, and platform infrastructure to enable repeatable, production-grade deployment.

Minimum Requirements

Education

• Bachelor's degree in Data Science, Computer Science, Statistics, Mathematics, Health Informatics, or a related quantitative field required.

Experience

• 10+ years of progressive experience in data science, machine learning, AI, or advanced analytics roles.
• 5+ years of leadership experience managing AI, machine learning, and/or data science teams, including leaders of managers.
• Proven track record of delivering production-grade AI, GenAI, and ML solutions within commercial products or platforms, with demonstrated customer impact.
• Experience operating in a high-growth, fast-paced environment (SaaS or healthcare technology strongly preferred).

Clinical Intelligence and Healthcare Domain Expertise

• Demonstrated background in clinical intelligence and/or clinical informatics, with experience building AI or analytics that support clinical decision-making, care management, or care coordination.
• Working knowledge of clinical data (EHR, claims, assessments, clinical notes) and healthcare standards and terminologies (e.g., FHIR, HL7, ICD-10, SNOMED, RxNorm).
• Understanding of care delivery workflows, how clinicians interact with decision support, and healthcare regulatory environments (HIPAA, clinical decision support, emerging AI regulation), with the ability to partner credibly with clinical leaders.

AI and Technical Expertise

• Hands-on, demonstrated experience with Generative AI, LLMs, and NLP, including deploying and evaluating multiple language models (commercial and open-source) in production.
• Strong understanding of LLM evaluation, safety, and quality methods, including RAG, fine-tuning, prompt engineering, agentic patterns, hallucination mitigation, and human-in-the-loop review.
• Deep expertise in machine learning, statistical modeling, and predictive analytics, with strong proficiency in Python (or R), ML frameworks (e.g., TensorFlow, PyTorch, scikit-learn), and modern LLM tooling.
• Experience building scalable solutions with open-source technologies in cloud environments (AWS, Azure, or GCP), with solid understanding of data engineering, model deployment, and MLOps/LLMOps, including monitoring, versioning, and CI/CD.
• Experience with model governance, bias and fairness assessment, explainability, and responsible AI practices.

Leadership and Communication

• Demonstrated ability to build, lead, and scale high-performing AI and data science teams, and to set vision and strategy for AI initiatives aligned to business goals.
• Proven ability to foster a culture of innovation, experimentation, and continuous improvement while maintaining high standards of quality.
• Strong cross-functional leadership skills, with experience partnering with product, engineering, clinical, and business stakeholders.
• Excellent verbal and written communication skills, with the ability to translate complex AI concepts into business value and customer impact, influence executive stakeholders, and present to non-technical audiences.
• Strong decision-making and problem-solving skills in ambiguous environments.

Work Environment

• Remote or Hybrid (Jacksonville/Nashville)

Preferred Skills and Experience

• Advanced degree (MS or PhD) preferred, ideally in a quantitative field or in health or clinical informatics.
• Experience in home-based care, hospice, post-acute, or value-based care preferred.

Physical Demands of Our Work Environment

This position uses a computer and other office equipment as needed to perform duties. The in-office noise level in the work environment is typical of that of an office. Frequent interruptions may be encountered throughout the workday.

The employee is required to either stand or sit, talk and hear frequently required to use repetitive keying or hand motions.

The physical demands 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.

Mosai is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, national origin, sex, sexual orientation, gender identity, veteran status, and disability, or other legally protected status, If you are unable to submit an application because of a incompatible assistive technology or disability, please contact us at careers@mosai.com. We will make every effort to respond to your request for disability assistance as soon as possible.

Mosai is an E-verify employer. Your eligibility to work in the United States will be verified through the E-verify system if you apply and are selected for a position.

**Be aware of employment fraud. All email communications from Mosai or its hiring managers originate from @mosai.com or <BambooHR recruiter email> addresses. We will never ask you for payment or require you to purchase any equipment. If you are suspicious or unsure about the validity of a job posting, we strongly encourage you to apply directly through our website.