Senior Data Scientist, RegLab - Stanford Law School

Stanford University School of Medicine; Palo Alto (CA); On-site; USD 117,000 - 130,000; Full time

Job summary

Stanford University School of Medicine’s Regulation, Evaluation, and Governance Lab (RegLab) seeks a Senior Data Scientist to advance public sector AI research. You will design AI models, lead projects, work with large, diverse data and mentor junior researchers, with co-authorship opportunities.

The position is full-time, one-year fixed term with potential extension based on performance, based in Palo Alto, CA, and offers opportunities to impact policy and practice in government analytics.

Qualifications

• Bachelor’s degree in data science, CS, stats, engineering, math, economics, or related field; 3 years of experience.
• Strong Python programming and debugging skills.
• Solid ML, NLP, and information retrieval experience on large/complex data.
• Experience with SQL and vector stores for structured/unstructured data.
• Experience building reliable data pipelines with data quality checks.
• Understanding of web security best practices for backend systems.
• Excellent written and verbal communication.

Responsibilities

• Collaborate with RegLab leadership to identify and implement research projects.
• Lead design and development of AI models and statistical methods for the public sector.
• Work with large, diverse data sets including health, environmental, and legal text.
• Mentor and manage other data scientists and junior researchers.
• Co-author research papers when opportunities arise.
• Create charts, databases, and analyses for publication and presentation.
• Communicate findings clearly to technical and non-technical audiences.

Skills

Python

Machine learning

NLP

Information retrieval

Data modeling

Data pipelines

Security best practices

Communication

Mentoring

Education

Bachelor's degree in a scientific/analytic field

MS or PhD preferred

Tools

SQL

Vector stores

GCP Cloud Run

Cloud SQL

Docker

Cloudflare Pages

Job description

• Excellent written and verbal communication, including documenting systems, decisions,

Job Description

Full Time

This is for a ONE-YEAR FIXED TERM position with the opportunity for extension based on performance.

Multiple Positions will be Filled

• Budgeted Range: The Law School’s budgeted pay for or this position is: $117,134 - $130,006 per annum.

The Regulation, Evaluation, and Governance Lab (RegLab) at Stanford University is looking for a Senior Data Scientist to help drive forward a diverse research program focused on public sector artificial intelligence (AI) applications and policy. We are looking for someone who has excellent technical skills, strong research expertise, good communication skills, and is motivated by the mission of the lab.

About Us: Stanford RegLab builds the evidence base and technology for effective government.

Our interdisciplinary team of engineers, data scientists, social scientists, and legal experts partners with agencies at every level—from federal departments to states, counties, and cities - bringing frontier AI, machine learning, and causal inference to the public sector.

RegLab’s work has prompted an overhaul of tax auditing, mapped racial covenants across millions of records, and enabled streamlining of statutes and regulations.

As Senior Data Scientist, You Will

• Work closely with the Faculty Director, research leadership, and the rest of the RegLab team to explore, identify, and implement research projects.
• Lead the design and development of multiple projects using state-of-the-art AI models, algorithms, statistical models, and other programs designed to improve the public sector.
• Work with large untapped data sets, such as: health and environmental enforcement data, mass adjudication records, high-resolution satellite imagery, and the largest publicly available corpus of legal text.
• Mentor and/or manage other data scientists and junior researchers.
• Have the opportunity to receive co-authorship on research papers.

Core Duties

• Collaborate with interdisciplinary research teams and external stakeholders to identify high-impact opportunities for applied data science in the public sector.
• Engage with partners to understand their data environments, help shape project goals, and ensure that technical outputs align with real-world needs and constraints.
• Adapt and refine existing AI models to align with the constraints and ethical considerations of public sector use cases, including fairness, transparency, and interpretability.
• Develop and test prototype software and participate in the approval and release process for new software.
• Prioritize and extract data from a variety of sources such as reports, legal documents, notes, survey results, and satellite imagery, and maintain its accuracy and completeness.
• Determine additional data collection and reporting requirements.
• Create complex charts and databases, perform statistical analyses, and develop graphs and tables for publication and presentation.
• Serve as a resource for non-routine inquiries such as requests for statistics or surveys.
• Provide documentation based on audit and reporting criteria to investigators and research staff.
• Communicate findings and technical insights clearly to both technical and non-technical audiences through reports, visualizations, presentations, and academic publications.

Preferred Qualifications

• A bachelor’s degree (MS or Ph.D. preferred) in a scientific or analytic field (e.g., data science, computer science, statistics, engineering, mathematics, economics, or a related field) and three years of (a) relevant professional experience or (b) combination of education and relevant professional experience.
• Strong programming skills in Python or a similar language, including debugging and writing maintainable code.
• Solid grounding in machine learning, NLP, and information retrieval methods, and experience applying them to large or complex datasets.
• Experience with data modeling and database systems for both structured and unstructured data (e.g., SQL, document or vector stores).
• Experience building reliable, scalable data pipelines with attention to data quality and validation, including evaluating new tools and frameworks.
• Understanding of security best practices for web applications and backend systems, such as authentication, access control, and handling sensitive data.
• Excellent written and verbal communication, including documenting systems, decisions, and recommendations for technical and non-technical audiences.

Nice To Haves

• Specialization in machine learning frameworks (TensorFlow, TF, PyTorch, Scikit Learn, etc.), NLP, LLM evaluation, LLM-assisted workflows, computer vision, or related fields
• Experience with cloud infrastructure and compute resources (e.g., GCP Cloud Run, Cloud SQL), including recommending tech stacks for research projects
• Familiarity with deploying containerized web applications (e.g., Docker, Cloudflare Pages), such as results dashboards or validation interfaces for partners to review LLM pipeline outputs

Responsibilities

• Prioritize and extract data from a variety of sources such as notes, survey results, medical reports, and laboratory data, and maintain its accuracy and completeness.
• Determine additional data collection and reporting requirements.
• Design and customize reports based upon data in the database. Oversee and monitor regulatory compliance for utilization of the data.
• Use system reports and analyses to identify potentially problematic data, make corrections, and eliminate root cause for data problems or justify solutions to be implemented by others.
• Create complex charts and databases, perform statistical analyses, and develop graphs and tables for publication and presentation.
• Serve as a resource for non-routine inquiries such as requests for statistics or surveys.
• Test prototype software and participate in approval and release process for new software.
• Provide documentation based on audit and reporting criteria to investigators and research staff.

Minimum Education

Bachelor's degree and three years of relevant experience or combination of education and relevant experience.

Minimum Experience

Experience in a quantitative discipline such as economics, finance, statistics or engineering.

Knowledge, Skills And Abilities

• Substantial experience with MS Office and analytical programs.
• Excellent writing and analytical skills.
• Ability to prioritize workload.