Data Science & AI Librarian

Data Science & AI Librarian This position is for a two-year limited term. Empirical insight and responsible data practices strengthen legal scholarship and public impact. The Data Science & AI Librarian empowers faculty and students with consultation and training in Python, NLP/LLM workflows, data acquisition and curation, and reproducible research. Partnering with campus data resources, this role advances rigorous, bias-aware analysis and preserves high-value datasets and code for long-term discovery and reuse. JOB PURPOSE The Data Science & AI Librarian is a key architect of the law school’s digital research future. This position applies technical expertise in programming and data science to solve complex legal information challenges, build innovative tools, and empower faculty and students to leverage computational methods. The incumbent will serve as the library's lead technical expert on data assessment and analysis, focusing on how data quality, structure, and bias function within AI models to ensure responsible and effective implementation of cutting-edge technologies. This position reports to the Associate Director for Access Services. CORE DUTIES • Formulates and implements library-wide policies or best practices for data science and AI services. • Serves as the library’s principal expert on emerging AI technologies, advising on their adoption and leading pilot projects. • Establish reproducible research practices (Git, environments/notebooks) and deposit datasets/code in campus repositories with rich documentation; assign persistent identifiers and apply metadata standards per repository policy. • Advise on research ethics/IRB and sensitive-data handling for AI/ML projects; coordinate with IRB where applicable. • Support the Reference & Instruction team by serving as the escalation path for complex data/AI queries, co-running office hours, creating internal playbooks and reusable notebooks, and training staff on RAG/verification to improve first-contact resolution. • Coordinates with and mentors other library staff in data and AI competencies to ensure these services are integrated across our research support teams. • Support LLM/NLP workflows (e.g., RAG pipelines, evaluation/guardrails) for legal text analytics; produce reusable evaluation notebooks (hallucination checks, citation validation, bias probes). • Design and teach technical skills workshops (Python/NLP, RAG, visualization, reproducibility). • Lead on data ethics, bias, and evaluation policy for AI in research contexts; publish guidance and checklists. • Assist with data acquisition (APIs, compliant web scraping, FOIA); cleaning/transforming; and analysis; advise on Data Management Plans for grants. • Liaise with campus data science institutes, HPC, and central library data services; use HPC or lightweight cloud runtimes when scale is needed. • Coordinate with the E-Resources Librarian to ensure text/data mining and API use comply with database licenses and robots/terms of use. • Teach or co-teach short courses or embedded modules on empirical legal methods, text analytics, and visualization. Participate in the shared AI & Innovation intake queue; triage and co-staff multi-facet projects. • Serve on the Library AI Advisory Group to align research practices with tool governance and classroom guidance. May supervise Data Scientists, Data Curators, and/or Data Assistants. Success Metrics: Number of faculty projects supported; Number of datasets/code deposited; Number of reproducible runs verified. OTHER DUTIES The statements above describe the general nature and level of work performed. They are not an exhaustive list of all responsibilities and duties. Duties, responsibilities, and activities may change, or new ones may be assigned, at any time at the University’s discretion. TECHNOLOGY SCOPE In addition to AI-specific platforms, this position will work with related (“AI-adjacent”) technologies and software. Examples may include: learning management and course tools (e.g., LMS/LTI integrations); legal research and discovery platforms; content management and web publishing; accessibility testing tools; analytics/dashboards; identity and access (e.g., Single Sign-On); APIs and light integrations; programming or notebook environments (e.g., Python/Jupyter); version control (e.g., Git); and service/ticket systems. Experience with any subset is welcome; training will be provided. Apply tot his job