Research Data Scientist

RTI International•Any RTI Office, NC

1d•$148,000 - $181,000

About The Position

RTI International is hiring a Research Data Scientist to apply advanced analytics—including artificial intelligence, machine learning, generative AI and large language models, and natural language processing—to complex research and operational challenges across RTI’s domains. The role works across health research and other areas such as social science, environmental research, economics, and defense, developing analytical approaches and software from prototypes through production while meeting scientific standards for transparency, validation, and reproducibility. The Research Data Scientist translates research questions and client needs into data-driven solutions and leads the design and development of analytical systems, AI/ML pipelines, interactive tools, and decision-support applications. The position independently leads data science architecture and analytical strategy on projects, contributes to business development and proposals, mentors staff, and represents RTI’s analytical capabilities to clients and professional audiences. It collaborates with researchers, software developers, clients, and other multidisciplinary partners, balancing exploratory research with production delivery. The anticipated hiring salary range is $148,000–$181,000. RTI describes its total rewards package as including paid time off, merit-based annual increases, bonus opportunities, recognition programs, insurance plans, a retirement savings program, paid parental leave, adoption or infertility expense assistance, education and development reimbursement, and an employee assistance program.

Requirements

Bachelor’s degree and at least 12 years of experience, or a master’s degree and at least 10 years of experience, or a PhD and at least 6 years of experience, or an equivalent combination of education and experience.
Demonstrated expertise in one or more advanced analytics or data science areas, such as AI/ML, generative AI and LLMs, NLP, or optimization, applied to complex research or client problems.
Strong proficiency in modern open-source data science programming languages, such as Python and/or R.
Working knowledge of shared version control using Git.
Experience using cloud-based analytical environments and collaborating with engineering teams to operationalize analytical or AI/ML workflows.
Excellent oral, written, and presentation skills, including the ability to explain AI system behavior, model limitations, and analytical findings to non-technical researchers and client stakeholders.
Strong interpersonal, collaboration, and mentoring skills, including the ability to provide technical leadership in multidisciplinary teams.
Experience contributing to proposals, technical writing, or business development in a research or client-contracting context.
Ability to analyze macro issues, think strategically, and communicate potential solutions to stakeholders.
Must be legally authorized to work in the United States and must not require now or in the future employment visa sponsorship.

Nice To Haves

AWS experience is preferred; experience with Azure, Google Cloud Platform, or equivalent is also applicable.
Domain expertise in health, omics, or life sciences; expertise in education, social sciences, energy research, or other RTI domains is also valuable.
Experience with multi-agent frameworks.
Experience with database systems such as PostgreSQL.
Interest in growing into project or people management leadership roles.
Experience with ETL pipelines and analyses involving varied data sources, including relational databases, text and unstructured files, sensor data, image/video data, and streaming data.
Experience with static and/or interactive data visualization methods and tools.

Responsibilities

Lead development of AI and machine-learning models, including NLP, generative AI and LLM systems, computer vision, decision systems, and software applications.
Lead technical work in data pipeline development and orchestration, data wrangling, ETL, exploratory data analysis, DataOps, MLOps, cloud computing, automation, rapid prototyping, and interactive data visualization.
Work within multidisciplinary teams and serve as Data Science Task Lead on projects as needed.
Work with researchers to identify, design, and iteratively improve domain-specific analytical applications and research workflow automation, including systematic review acceleration, survey coding, proposal knowledge management, and research data quality assurance.
Lead evaluation frameworks and quality assurance for AI/ML systems, including regression testing, human-in-the-loop evaluation, cost and quality monitoring, and safety assessment.
Assess proposal opportunities, participate in Capture Teams and opportunity assessments, lead proposals for small to medium opportunities, write proposal sections, review proposals, and contribute to technical and budget volumes.
Frame, design, and estimate data science solutions based on client needs.
Lead meetings with internal and external clients, translate needs into data science solutions, and represent RTI’s capabilities in professional and scientific settings.
Present at conferences, contribute to refereed publications, and write blog posts and impact stories.
Mentor data science staff; lead code and design reviews and knowledge-transfer sessions; and participate in hiring and interviews.
Lead internal innovation initiatives, represent data science to RTI leadership, identify infrastructure, process, and skills gaps, and propose solutions.