Data Science & AI Librarian, Stanford Law School
School of Law, Stanford, California, United States
New
Library
Post Date 5 hours ago
Requisition # 107438
This is a Hybrid position.
This position is for a two-year limited term.
NOTE: This position has been deemed critical/has specific funding, has been approved by the Law School for posting, and is exempt from the hiring freeze.
Data Science & AI Librarian
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.
MINIMUM REQUIREMENTS:
Recommended Education & Experience:
Master's degree in one of: Library/Information Science (ALA-accredited), Computer Science, Data Science, Statistics, Information Science, or a closely related field; or an equivalent combination of education and experience (e.g., 3+ years applied data science supporting academic or legal research).
Portfolio required (GitHub/notebooks or comparable) demonstrating Python/NLP, data management, and reproducible research practices.
Familiarity with legal information sources and research workflows strongly preferred; JD not required.
Knowledge, Skills and Abilities:
Required
Demonstrated experience with Python and its libraries relevant to data analysis or machine learning (e.g., Pandas, Scikit-learn).
Strong understanding of AI concepts, including machine learning, and experience with data assessment methodologies.
Documented experience in providing technical training or consultations.
Preferred
Familiarity with legal information sources and research processes.
Experience orchestrating LLM workflows (e.g., RAG pipelines, evaluation/guardrails) and working with tools like Jupyter; familiarity with Git for collaboration.
Knowledge of data management plans and reproducible research practices.
Experience with data visualization tools (e.g., Tableau).
Hands-on experience with NLP/LLM tooling such as spaCy and Hugging Face; ability to build RAG notebooks and run small evaluations.
Orchestration frameworks familiarity such as LangChain or LlamaIndex for rapid proto@types.
Proficiency with tools like Jupyter ,GitHub , and environment management for reproducible workflows.
Proficiency with SQL and API data acquisition patterns; light web scraping with ethics/compliance awareness.
Comfortable packaging a project so it runs the same on any machine (Docker) and, when a laptop isn't enough, using campus high-performance computing (HPC) or a small cloud server to process larger datasets or speed up jobs.
PHYSICAL REQUIREMENTS, WORKING CONDITIONS, & WORK STANDARDS:
Physical Requirements: Primarily a sedentary role involving desk-based computer tasks. May occasionally lift or move objects up to 10 pounds. Consistent with its obligations under the law, the University will provide reasonable accommodations to any employee with a disability who requires an accommodation to perform the essential functions of the job.
Working Conditions : Work is performed in a typical office environment. May work extended hours, evenings, and weekends as needed to complete projects or support events.
Work Standards:
Interpersonal Skills : Demonstrates the ability to work well with colleagues and clients and with external organizations.
Promote Culture of Safety : Demonstrates commitment to personal responsibility and value for safety; communicates safety concerns; uses and promotes safe behaviors based on training and lessons learned.
Subject to and expected to comply with all applicable University policies and procedures.
Benefits & Professional Development:
We are committed to the well-being and growth of our staff. This position includes a comprehensive benefits package, effective on the first day of employment, featuring:
Health & Wellness : Multiple medical, dental, and vision plans; health savings and flexible spending accounts; and access to wellness facilities and financial incentives.
Retirement : A generous 403(b) retirement plan with university contributions and matching.
Time Away : Substantial paid time off, including vacation, 11 paid holidays, a two-week winter closure, sick leave, and baby bonding leave.
Professional Growth : An annual professional development stipend and a tuition reimbursement program for degree programs.
Work/Life Balance : Programs to support a healthy work/life balance, including child care subsidy grants, back-up dependent care, and free commute passes.
The expected pay range for this position is $140,758 - $177,489 per annum.
Stanford University provides pay ranges representing its good faith estimate of what the university reasonably expects to pay for a position. The pay offered to a selected candidate will be determined based on factors such as (but not limited to) the scope and responsibilities of the position, the qualifications of the selected candidate, departmental budget availability, internal equity, geographic location and external market pay for comparable jobs.
At Stanford University, base pay represents only one aspect of the comprehensive rewards package. The Cardinal at Work website(https://cardinalatwork.stanford.edu/benefits-rewards) provides detailed information on Stanford's extensive range of benefits and rewards offered to employees. Specifics about the rewards package for this position may be discussed during the hiring process.
Additional Information
Schedule: Full-time
Job Code: 1784
Employee Status: Fixed-Term
Grade: K
Requisition ID: 107438
Work Arrangement : Hybrid Eligible
