Back
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Known analytics brand, mid-level experience, metro location, and general Data Scientist title raise applicant competition.
Agentic AI and SAS domain expertise increases specialization, making cross-industry transfer moderately sensitive.
Explicit 3–8 years, MSc/PhD, mandatory SAS and agentic-AI skills, and CI/CD make filters strict.
Design, build, and deploy agentic AI solutions involving multi-step reasoning agents, tool-using systems, and workflow automation to solve business and scientific problems.
Develop, maintain, and ensure quality of SAS programs and pipelines with regulatory or clinical data standards, including unit testing and CI/CD pipelines for automated testing and deployment.
Collaborate with cross-functional teams to translate requirements into scalable AI solutions and evaluate emerging open-source AI/ML techniques for applicability.
MSc/Ph.D. in Statistics or Mathematics with 3-8 years of relevant experience.
Strong programming proficiency in SAS (Base SAS/Macro) and Python, including agentic AI frameworks, LLM orchestration, and API integration.
Demonstrated experience in agentic AI system development (LLM-based agents, tool-calling, RAG, multi-agent orchestration, or similar).
Hands-on experience with unit testing, test-driven development, Git, CI/CD pipelines, and deployment of models into production.
Strategic thinker with a research-oriented approach capable of prototyping and validating AI techniques before production scaling.
Experienced in combining traditional statistical workflows with modern AI-driven approaches, backed by strong statistical foundations.
Comfortable working in regulated or clinical data environments and collaborating across data science, engineering, and domain expert teams.