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Stanford University Senior Data Scientist, School of Law in Stanford, California

Senior Data Scientist, School of Law

School of Law, Stanford, California, United States

New

Information Analytics

Post Date 5 days ago

Requisition # 103711

*Note: Only internal candidates are being considered for this position.

DESCRIPTION:

Stanford Securities Litigation Analytics is a research center within Stanford Law School focusing on public company shareholder litigation and corporate governance matters. SSLA closely collaborates with legal practitioners and risk managers to pursue research questions with practical applications. SSLA seeks a Senior Data Scientist to lead its research and experimentation on applications of artificial intelligence, natural language processing and machine learning to extract securities litigation data from court documents and other sources. Key tasks will include analysis and data extraction from legal texts, developing and refining frequency and severity models for litigation, and developing pipelines to integrate AI & machine learning into the larger project workflow. The Senior Data Scientist will advise Professor Michael Klausner and Executive Director Jason Hegland regarding the trends and advancements in this field. In addition, the Senior Data Scientist will support the work of the current research team by managing existing case data, assisting with quality assurance, and creating data visualizations to help our researchers communicate their findings and ideas.

The Senior Data Scientist will report to SSLA Fellow & Research Manager David Gonyer within the SSLA org structure and with a dotted-line reporting relationship with Stanford Law School’s IT department to ensure compliance with SLS policies related to AI tools and collaboration across departments through quarterly meetings. The Senior Data Scientist will supervise a Data Scientist.

DUTIES:

  • Prioritize, extract, and clean data from a variety of sources such as WRDS, SPAC Insider, and NASDAQ, in addition to legal texts such as complaints, using Python, Stata, and R.

  • Evaluate results of text extraction programs and identify additional data necessary to increase accuracy and precision of programs

  • Design and customize query-specific reports and data visualizations in conjunction with research team and review draft reports prepared by Data Scientist.

  • Use system reports and analyses to identify potentially problematic data in SSLA’s database or data extracted from legal texts; revise code or text collection techniques to increase data quality

  • Utilize R, Python, HighCharts, and Excel to prepare summary statistics and produce visualizations of multivariate data for use in blog posts, industry publications, and other projects.

  • Serve as main point of contact for data-related questions from research team and project data licensees; provide ongoing training and guidance to Data Scientist

  • Assist SSLA research team with documentation of data collection protocols and quality assurance checks

QUALIFICATIONS:

  • Bachelor’s degree and three years of relevant experience or combination of education and relevant experience

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

  • Quantitative master’s degree preferred

  • Prior experience with AI & machine learning preferred

  • Prior experience with complex litigation and legal texts preferred

Knowledge, Skills and Abilities:

  • Substantial experience with MS Office and analytical programs.

  • Excellent writing and analytical skills.

  • Ability to prioritize workload.

*The expected pay range for this position is $86,000 to $126,000 per annum in the Stanford Work Location

*The expected pay range for this position is $72,000 to $103,000 per annum in a Remote Work Location

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.

*Note: The job duties listed are typical examples of work performed by positions in this job classification and are not designed to contain or be interpreted as a comprehensive inventory of all duties, tasks, and responsibilities. Specific duties and responsibilities may vary depending on department or program needs without changing the general nature and scope of the job or level of responsibility. Employees may also perform other duties as assigned.

*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.

*Stanford is an equal employment opportunity and affirmative action employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, protected veteran status, or any other characteristic protected by law.

*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.

Additional Information

  • Schedule: Full-time

  • Job Code: 4752

  • Employee Status: Regular

  • Grade: I

  • Department URL: http://www.law.stanford.edu/

  • Requisition ID: 103711

  • Work Arrangement : Hybrid Eligible, Remote Eligible

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