Health Data Scientist 3- AI Solutions

The Opportunity

As a Health Data Scientist III- AI Solutions you will support clients and project teams in applying artificial intelligence, machine learning, and advanced analytics to real-world operational, programmatic, and analytical challenges. This role combines hands-on technical work, client-facing collaboration, and practical problem solving to help develop AI-enabled solutions that improve decision-making, increase efficiency, and support measurable impact.

You will work with project teams, clients, senior technical staff, and business development colleagues to identify appropriate opportunities for AI application, build prototypes and analytical solutions, and contribute to innovative approaches for new business opportunities. Initially, this role will focus on health-related programs and growth opportunities spanning public health, healthcare delivery, justice programs and behavioral health, and health systems research.

This position is ideal for a technically strong, collaborative professional who enjoys translating real-world problems into practical AI and data science solutions, working closely with stakeholders, and continuing to grow expertise across implementation, client engagement, and applied innovation.

Key Roles and Responsibilities

AI and Data Science Solutions

• Support the design, development, testing, and implementation of AI, machine learning, and advanced analytics solutions that address client needs in healthcare, public health, and justice systems.
• Build, test, and refine predictive models, natural language processing solutions, and generative AI applications under the guidance of senior technical staff.
• Develop prototypes, proofs of concept, and practical applications using modern AI technologies, with support in moving successful concepts toward broader implementation.
• Apply large language models (LLMs), retrieval-augmented generation (RAG), agentic AI concepts, and machine learning techniques to defined business and program challenges.
• Contribute to data pipelines, model evaluation approaches, and analytical workflows that support reliable and scalable solutions, for government data, with focus on public health, healthcare, and justice systems.
• Follow and contribute to responsible AI practices, including model testing, validation, documentation, governance, and risk mitigation.

Client Engagement and Solution Development

• Collaborate with project teams and clients to identify opportunities where AI and advanced analytics can improve outcomes
• Translate business requirements into technical options, analytical approaches, and solution designs in collaboration with project leads and technical experts.
• Participate in solutioning sessions, demonstrations, workshops, and discovery activities.
• Communicate technical concepts and analytical findings to both technical and non-technical audiences.
• Support implementation, testing, user feedback, and adoption of AI-enabled tools and solutions.

Health Analytics and Innovation

• Apply data science and AI techniques to health, public health, healthcare, and global health challenges.

• Analyze structured and unstructured data to generate insights and improve organizational performance.
• Support development of AI-enabled approaches for: 

• Public health and epidemiological analytics
• Program monitoring and evaluation
• Healthcare operations and service delivery
• Knowledge management and information retrieval
• Research synthesis and evidence generation
• Workflow automation and decision support

Business Development and Growth Support

• Participate in development of demonstrations, prototypes, and AI capabilities for client pursuits.
• Monitor emerging AI technologies and approaches and share ideas for how they could strengthen client solutions or business opportunities.
• Help develop and maintain reusable AI assets, accelerators, templates, and solution frameworks.

Professional Development and Collaboration

• Stay current on developments in artificial intelligence, machine learning, and data science.
• Share knowledge, best practices, and practical lessons learned with colleagues, project teams, and communities of practice.
• Collaborate across disciplines including health experts, researchers, engineers, software developers, and business development professionals.

What We Value

• Bachelor's Degree plus five years of relevant experience, or Master's Degree plus three years of relevant experience.

• Degree in Data Science, Computer Science, Statistics, Applied Mathematics, Engineering, Bioinformatics, Health Informatics, or a related quantitative field.
• Applied experience developing, testing, or improving machine learning, artificial intelligence, or advanced analytics solutions in professional or project-based environments.
• Proficiency programming in Python and using common data science libraries and frameworks.
• Strong skills in data analytics/data science, and data management languages, particularly Python, SAS, R, and SQL.
• Skills in Databricks, Snowflake, Github, AWS, Ask Sage/LLM’s, and FTP. Experience with AI coding companion tools such as github copilot
• Experience preparing, analyzing, and interpreting structured and unstructured data sources.
• Ability to explain analytical methods, findings, and technical tradeoffs to both technical and non-technical audiences.
• Demonstrated problem-solving and critical-thinking skills.
• Experience working collaboratively in multidisciplinary teams.
• Working knowledge of generative AI technologies, such as LLMs, prompt engineering, retrieval-augmented generation, or AI agents.
• Familiarity with cloud environments such as Azure, AWS, or Google Cloud.
• Familiarity with MLOps, model evaluation, model deployment concepts, and software engineering best practices.
• Experience or demonstrated interest in applying analytics, AI, or data science to healthcare, public health, global health, or health research programs.
• Experience contributing technical inputs, prototypes, or solution ideas for proposals, capture efforts, or new business opportunities.
• Familiarity with health data standards, healthcare analytics, digital health ecosystems, or related health data environments.
• Experience developing or supporting client-facing dashboards, analytical products, decision-support tools, or similar data products.
• Able to obtain and maintain public trust access for HHS information systems (e.g. CMS, BJS)