Senior Data Scientist, RegLab - Stanford Law School

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

How to apply

• There will be two rounds of application review. The deadline for the first round is 7:00AM PST
• on Friday, October 30, 2026. All applications received before this date are guaranteed to be read
• while there is a spot open. After this date we will still be accepting applications received by
• December 1, however preference will be given to first round applications.
• Applicants with Optional Practical Training (OPT) temporary employment authorization are
• eligible to apply. Depending on the circumstances, Stanford may sponsor J-1 visas for this
• position.
• There is a two-step process to be considered for this fellowship:

• Please submit your resume and cover letter when you apply through Stanford’s career

site – reference job number: 201360

• Additionally, upload all of the following here https://reglab.stanford.edu/work-with-

us/.

• Brief cover letter explaining your interest in the position
• Current resume or CV
• Transcript (unofficial version acceptable)
• Writing/code sample

Core Duties

• 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.