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Software engineer
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Senior Data Scientist, RegLab - Stanford Law School
- Posted
- 1MO AGO
About the role
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:
1. Please submit your resume and cover letter when you apply through Stanford’s career site – reference job number: 201360
2. 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.
