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AI Data Scientist-Furman lab
Job Location:
Job Location:
Novato, CA - USA
Yearly Salary:
USD 60000 - 75000
Yearly Salary:
Posted:
12 June 2026 (30+ days ago)
Posted:
Application Deadline:
9 September 2026
Application Deadline:
Vacancies:
1 Vacancy
Vacancies:
Job Summary
Position Summary
The 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 Masters 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 Responsibilities
1. 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:
Responsibilities may include:
The candidate may contribute to analyses involving:
The candidate will work closely with computational biologists data scientists principal investigators research staff software engineers and external collaborators. Responsibilities may include:
Required Education and Experience
Our 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 Alzheimers disease Parkinsons 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 Apply
Interested candidates should click the Apply button to complete the online application.
Please upload:
The 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 Masters 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 Responsibilities
1. 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 analysis
- Designing LLM-powered tools to help harmonize large datasets across cohorts studies institutions and assay platforms
- Building pipelines to extract standardize and validate metadata and data dictionaries
- Creating systems to support multi-modal data integration across omics clinical demographic imaging and functional datasets
- Developing scalable approaches for identifying patterns inconsistencies and missing information across large datasets
- Supporting model development for prediction classification clustering and biological interpretation
- Prototyping AI tools that improve research productivity reproducibility and scientific discovery
Responsibilities may include:
- Building workflows using large language models retrieval-augmented generation vector databases tool-calling agents and automated reasoning systems
- Designing AI agents capable of interacting with structured and unstructured scientific data
- Developing systems that assist with literature mining data annotation hypothesis generation and biological interpretation
- Evaluating the performance limitations and reliability of AI-enabled tools in biomedical research contexts
- Supporting responsible reproducible and well-documented use of AI in federally funded research
- Collaborating with bioinformaticians and domain experts to translate research needs into functional computational tools
The candidate may contribute to analyses involving:
- Transcriptomics including single-cell and bulk RNA-seq
- Proteomics
- Metabolomics
- Epigenetics and biological aging clocks
- Clinical and phenotypic datasets
- Survey data
- Integrative multi-omics
- Dimensionality reduction and clustering
- Classification methods and predictive modeling
- Drug repurposing
- Network analysis and pathway enrichment
- Computer vision and feature extraction as applicable
The 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 workflows
- Participating in project meetings and presenting technical progress
- Creating clear documentation diagrams and technical specifications
- Supporting manuscript preparation grant writing figure generation and reporting
- Working with diverse teams to improve data transfer management and analysis systems
- Helping establish best practices for AI-assisted data science in biomedical research
Required Education and Experience
- Masters 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 considered
- Demonstrated experience building AI data science machine learning or software engineering systems
- Strong proficiency in Python
- Experience using large language models AI APIs or LLM-based developer tools
- Experience with modern software engineering practices version control testing documentation and collaborative development
- Ability to work independently rapidly prototype solutions and solve ambiguous technical problems
- Strong practical experience with large language models and AI-assisted workflows
- Interest or experience in agentic AI tool-calling agents retrieval-augmented generation vector search or automated workflow orchestration
- Strong analytical and problem-solving skills
- Ability to design systems for organizing harmonizing and modeling large datasets
- Comfort working with structured and unstructured data
- Excellent written and oral communication skills
- Strong attention to detail and commitment to reproducibility
- Ability to collaborate with both technical and non-technical team members
- High degree of creativity initiative and intellectual curiosity
- Evidence of exceptional technical achievement such as hackathon wins awards competitive programming startup experience open-source contributions publications deployed products or other high-impact projects
- Experience with biomedical healthcare clinical or omics data
- Experience with APIs cloud platforms Docker databases or scalable data systems
- Experience with vector databases embeddings RAG systems or AI agent frameworks
- Experience with Python-based data science libraries and machine learning frameworks
- Familiarity with data harmonization metadata standards ontologies or research data repositories
- Experience working in fast-paced startup academic or highly collaborative environments
- Salary range: $60000$75000 commensurate with experience
- Full-time position
- Exciting collaborative work environment at the forefront of aging research AI and computational biology
- Opportunity to help build AI-enabled systems for large-scale biomedical discovery
- Generous benefits package including:
- Health insurance
- Paid parental leave
- Generous paid time off
- 401(k) with 5% employer match
- Work visa sponsorship may be available for qualified candidates
Our 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 Alzheimers disease Parkinsons 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 Apply
Interested candidates should click the Apply button to complete the online application.
Please upload:
- Resume or CV
- A brief statement describing your technical interests relevant AI/data science experience and examples of systems tools or projects you have built
- Names and contact information for three references if available
Required Experience:
Senior IC
