Senior Data Scientist, RegLab, Stanford Law School
The Regulation, Evaluation, and Governance Lab (RegLab) at Stanford University is looking for a Senior Data Scientist to provide big data architecture and analytical expertise across our research programs.
About Us: Stanford’s RegLab is a social impact lab that partners with government and nonprofits to use machine learning and data science to modernize the public sector. We are an interdisciplinary team of lawyers, data scientists, social scientists, and engineers who are passionate about building high impact demonstration projects for the future of governance. Some of our partners include the EPA, IRS, and Santa Clara County Public Health (Covid-19 response).
- Report to the Faculty Director, and work closely with the Head of Data Science, and teams of fellows and students to drive forward a diverse research program focused on machine learning and policy evaluation.
- Develop and devise state-of-the-art machine learning models, algorithms, and statistical models, while leading the collection of new data and the refinement of existing data sources.
- Work with large untapped data sets, including: health and environmental enforcement data, mass adjudication records, high-resolution satellite imagery (15cm/pixel), and the largest publicly available corpus of legal text.
- Design data systems that are scalable, optimized and fault-tolerant, and work closely with researchers and project managers to understand data requirements for existing and future projects
- Develop, test, implement, and maintain data management systems. Optimize and tune the system, perform software review and maintenance to ensure that data design elements are reusable, repeatable and robust.
- Contribute to the development of guidelines, standards, and processes to ensure data quality, integrity and security of systems and data appropriate to risk
- Participate in and/or contribute to setting strategy and standards through data architecture and implementation and leveraging analytics tools and technologies
- Research and suggest new toolsets/methods to improve data ingestion, storage, and data access
- Have the opportunity to receive co-authorship on research papers
- 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 five years of (a) relevant professional experience or (b) combination of education and relevant professional experience.
- Expert knowledge of programming languages (such as Python, R, and/or SQL) and ability to research, evaluate, architect, and deploy new tools and frameworks
- A deep understanding of modern statistical and machine learning models, when to apply them, and how to evaluate their performance
- Knowledge of key data structures algorithms, and techniques pertinent to systems that support high volume, velocity, or variety datasets (including data mining, machine learning, NLP, data retrieval).
- Experience with relational, NoSQL, or NewSQL database systems and data modeling, structured and unstructured.
- Experience in parallel and distributed data processing techniques and platforms (MPI, Map/Reduce, Batch).
- Experience in scripting languages and experience in debugging them, experience with high performance/systems languages and techniques.
- Knowledge of benchmark software development and programmable fields/systems, ability to analyze systems and data pipelines and propose solutions that leverage emerging technologies.
- Ability to use and integrate security controls for web applications, mobile platforms, and backend systems.
- Experience deploying reliable data systems and data quality management.
- Ability to research, evaluate, architect, and deploy new tools, frameworks, and patterns to build scalable Big Data platforms.
- Ability to document use cases, solutions and recommendations.
- Demonstrated excellence in written and verbal communication skills.
- Self-guided, self-learner, and engaged in the mission of the Lab.
Nice to Haves:
- Specialization in machine learning frameworks (TensorFlow, TF, PyTorch, Scikit Learn, etc.), NLP, computer vision, or related fields
- Academically-minded, with experience working in an academic setting
Consistent with its obligations under the law, the University will provide reasonable accommodation to any employee with a disability who requires accommodation to perform the essential functions of the job.
Application Instructions: We invite you to apply by clicking on the "Apply for Job" button found on the cardinal careers website found here. To be considered, please submit the following items along with your online application:
- Project and code samples or Github
Stanford is an equal employment opportunity and affirmative action employer.
Stanford Law School seeks to hire the best talent and to promote a safe and secure environment for all members of the university community and its property. To that end, new staff hires must successfully pass a background check prior to starting work at Stanford University.
- Schedule: Full-time
- Job Code: 4734
- Employee Status: Regular
- Grade: K
- Department URL: http://www.law.stanford.edu/
- Requisition ID: 88037