Lead AI/ML Data Scientist for Health Research & NLP

RTI International; Durham (NC); On-site; USD 148,000 - 181,000; Full time

Job summary

RTI International seeks a Data Scientist to lead analytics across AI/ML, NLP, and LLM projects, applying advanced methods to health research and other RTI domains. You will mentor staff, shape proposals, and collaborate with researchers, software developers, and clients to deliver production-ready analytics solutions.

You will drive design of AI systems, evaluation frameworks, and data platforms, ensuring transparency, validation, and reproducibility while partnering with cross-disciplinary

Qualifications

• Demonstrated expertise in AI/ML, NLP, or optimization with applications to research or client problems.
• Strong proficiency with Python and/or R for data science.
• Experience collaborating with multidisciplinary teams and stakeholders.

Responsibilities

• Lead development of AI/ML models, including NLP and LLM-based systems.
• Oversee data pipeline development, data wrangling, ETL, and data visualization.
• Mentor data science staff and contribute to proposals and business development.
• Represent RTI's data science capabilities in professional settings.
• Develop evaluation frameworks and ensure quality and reproducibility of AI outputs.

Skills

AI/ML expertise

NLP & LLMs

Python/R

Cloud computing (AWS)

Data visualization

Excellent communication

Mentoring

Git version control

Education

Bachelor's degree with extensive experience

Master's degree with extensive experience

PhD with substantial experience

Tools

Git

PostgreSQL

ETL pipelines

Data visualization tools

Job description

RTI International seeks a Data Scientist to lead analytics across AI/ML, NLP, and LLM projects, applying advanced methods to health research and other RTI domains. You will mentor staff, shape proposals, and collaborate with researchers, software developers, and clients to deliver production-ready analytics solutions.

You will drive design of AI systems, evaluation frameworks, and data platforms, ensuring transparency, validation, and reproducibility while partnering with cross-disciplinary