AI Data Scientist-Furman lab

Key Responsibilities

• Develop AI-enabled systems for large-scale data harmonization and modeling
• Design agentic AI workflows to support data curation, quality control, documentation, and analysis
• Design LLM-powered tools to help harmonize large datasets across cohorts, studies, institutions, and assay platforms
• Create systems to support multi-modal data integration across omics, clinical, demographic, imaging, and functional datasets
• Develop scalable approaches for identifying patterns, inconsistencies, and missing information across large datasets
• Support model development for prediction, classification, clustering, and biological interpretation
• Prototype AI tools that improve research productivity, reproducibility, and scientific discovery

Qualifications

• Master’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 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
• 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