AI Data Scientist-Furman lab

Position SummaryThe Buck Institute for Research on Aging is seeking an exceptional, highly motivated AI Data Scientist / Agentic AI Engineer to join a collaborative research team focused on aging, computational biology, multi-omics, and translational data science.This position is ideal for a creative, technically outstanding individual with a Master’s degree or equivalent experience who has demonstrated excellence through high-impact projects, awards, hackathons, publications, startup experience, open-source contributions, or other evidence of exceptional technical ability. We are especially interested in candidates who are deeply fluent in the use of large language models, agentic AI systems, modern software engineering practices, and scalable approaches for harmonizing and modeling large, complex datasets.The successful candidate will contribute to multiple government-funded and institutional research initiatives, including a recently launched, government-funded project focused on using large-scale human data to better understand biological aging, resilience, healthspan, and age-related disease risk. This role will help develop innovative AI-enabled systems for organizing, harmonizing, analyzing, modeling, and interpreting large datasets generated across multiple collaborators, institutions, platforms, and data types.We are looking for someone who is not only technically strong, but also inventive, entrepreneurial, and capable of rapidly building solutions. The ideal candidate will be comfortable working at the intersection of AI, software engineering, data science, and biomedical research, and will bring the creativity needed to design new approaches for managing and modeling complex scientific data.Key Responsibilities2. Apply LLMs, agentic AI, and modern machine learning approaches to biomedical research Develop AI-enabled systems for large-scale data harmonization and modeling The candidate will help design, build, and implement computational systems that support the organization, harmonization, modeling, and interpretation of large biomedical datasets. Responsibilities may include:Developing agentic AI workflows to support data curation, quality control, documentation, and analysisDesigning LLM-powered tools to help harmonize large datasets across cohorts, studies, institutions, and assay platformsBuilding pipelines to extract, standardize, and validate metadata and data dictionariesCreating systems to support multi-modal data integration across omics, clinical, demographic, imaging, and functional datasetsDeveloping scalable approaches for identifying patterns, inconsistencies, and missing information across large datasetsSupporting model development for prediction, classification, clustering, and biological interpretationPrototyping AI tools that improve research productivity, reproducibility, and scientific discoveryResponsibilities may include:Building workflows using large language models, retrieval-augmented generation, vector databases, tool-calling agents, and automated reasoning systemsDesigning AI agents capable of interacting with structured and unstructured scientific dataDeveloping systems that assist with literature mining, data annotation, hypothesis generation, and biological interpretationEvaluating the performance, limitations, and reliability of AI-enabled tools in biomedical research contextsSupporting responsible, reproducible, and well-documented use of AI in federally funded researchCollaborating with bioinformaticians and domain experts to translate research needs into functional computational tools3. Support large-scale data science and computational biology projectsThe candidate may contribute to analyses involving:Transcriptomics, including single-cell and bulk RNA-seqProteomicsMetabolomicsEpigenetics and biological aging clocksClinical and phenotypic datasetsSurvey dataIntegrative multi-omicsDimensionality reduction and clusteringClassification methods and predictive modelingDrug repurposingNetwork analysis and pathway enrichmentComputer vision and feature extraction, as applicable4. Collaborate across interdisciplinary teamsThe candidate will work closely with computational biologists, data scientists, principal investigators, research staff, software engineers, and external collaborators. Responsibilities may include:Translating scientific goals into computational tools and workflowsParticipating in project meetings and presenting technical progressCreating clear documentation, diagrams, and technical specificationsSupporting manuscript preparation, grant writing, figure generation, and reportingWorking with diverse teams to improve data transfer, management, and analysis systemsHelping establish best practices for AI-assisted data science in biomedical researchQualificationsRequired Education and ExperienceMaster’s degree in Computer Science, Data Science, Computational Biology, Bioinformatics, Applied Mathematics, Statistics, Engineering, or a related field; equivalent professional, entrepreneurial, or technical experience will also be consideredDemonstrated experience building AI, data science, machine learning, or software engineering systemsStrong proficiency in PythonExperience using large language models, AI APIs, or LLM-based developer toolsExperience with modern software engineering practices, version control, testing, documentation, and collaborative developmentAbility to work independently, rapidly prototype solutions, and solve ambiguous technical problemsRequired SkillsStrong practical experience with large language models and AI-assisted workflowsInterest or experience in agentic AI, tool-calling agents, retrieval-augmented generation, vector search, or automated workflow orchestrationStrong analytical and problem-solving skillsAbility to design systems for organizing, harmonizing, and modeling large datasetsComfort working with structured and unstructured dataExcellent written and oral communication skillsStrong attention to detail and commitment to reproducibilityAbility to collaborate with both technical and non-technical team membersHigh degree of creativity, initiative, and intellectual curiosityPreferred QualificationsEvidence of exceptional technical achievement, such as hackathon wins, awards, competitive programming, startup experience, open-source contributions, publications, deployed products, or other high-impact projectsExperience with biomedical, healthcare, clinical, or omics dataExperience with APIs, cloud platforms, Docker, databases, or scalable data systemsExperience with vector databases, embeddings, RAG systems, or AI agent frameworksExperience with Python-based data science libraries and machine learning frameworksFamiliarity with data harmonization, metadata standards, ontologies, or research data repositoriesExperience working in fast-paced startup, academic, or highly collaborative environmentsCompensation And BenefitsSalary range: $60,000–$75,000, commensurate with experienceFull-time positionExciting, collaborative work environment at the forefront of aging research, AI, and computational biologyOpportunity to help build AI-enabled systems for large-scale biomedical discoveryGenerous benefits package, including:Health insurancePaid parental leaveGenerous paid time off401(k) with 5% employer matchWork visa sponsorship may be available for qualified candidatesAbout The Buck InstituteOur success will ultimately change healthcare. At the Buck Institute for Research on Aging, we aim to end the threat of age-related diseases for this and future generations by bringing together the most capable and passionate scientists from a broad range of disciplines to identify and impede the ways in which we age.The Buck is an independent, nonprofit institution located in Marin County, California, with the goal of increasing human healthspan, or the healthy years of life. Globally recognized as a pioneer and leader in efforts to target aging — the number one risk factor for diseases including Alzheimer’s disease, Parkinson’s disease, cancer, macular degeneration, heart disease, and diabetes — the Buck seeks to help people live better longer.We are an equal opportunity employer and strive to create an atmosphere where diversity of identity, experience, and background are welcomed, valued, and supported. Candidates who contribute to this diversity are strongly encouraged to apply.To ApplyInterested candidates should click the Apply button to complete the online application.Please upload:Resume or CVA brief statement describing your technical interests, relevant AI/data science experience, and examples of systems, tools, or projects you have builtNames and contact information for three references, if available