Research Data Analyst 2

Manage and analyze large amounts of information, which is typically technical or scientific in nature including creating large and complex data sets, abstracting and formatting data, importing and exporting data between files, performing statistical analysis, and preparing reports and manuscripts for publication.

Who We Are

The Stanford Graduate School of Education (GSE) is dedicated to solving education's greatest challenges. Through rigorous research, model training programs and partnerships with educators worldwide, we're pursuing equitable, accessible and effective learning for all. The GSE is a top-ranked school of education, known for its prestigious faculty, rigorous graduate degree programs, and its impact on the quality of education across the world. The GSE is committed to developing leaders in education research, practice and policy.

Our community includes over 60 faculty, 400 students, 230 staff, 14,000 alumni and countless individuals from the local and global communities that we work with and impact.

The Educational Opportunity Project (EOP), housed in the Graduate School of Education, is seeking a Research Data Analyst 2. The EOP is dedicated to measuring educational opportunity in every community in America and has built the most comprehensive national database of academic performance in the U.S., the Stanford Education Data Archive (SEDA).

This position will support work to expand and improve SEDA through contributing to the development and implementation of new linking and estimation methods, the cleaning and integration of new years of data into SEDA, the release of new metrics in the database, and analyses of the SEDA data.

About the Role

The Research Data Analyst 2 will work closely with the Executive and Faculty Directors of the EOP to develop code to clean, organize, and harmonize data from large longitudinal education datasets; to implement statistical estimation methods; and to analyze data for research publications. This position requires independent work as well as collaboration with the EOP team. Significant experience using Stata, a strong statistical background, and careful attention to detail is critical for this role.

This position is a 1-year fixed term appointment with annual renewal contingent on available funds. The position is based on Stanford University’s main campus. Consideration will be given to a hybrid work schedule (partially onsite and offsite work), subject to operational need. Interested candidates should include a resume and cover letter describing why they are interested in this position at this stage in their career.

The expected pay range for this position is $91,852 to $128,138 per annum.

Areas of Focus

Extract and clean data from a variety of sources, including state departments of education and the federal government, and maintain its accuracy and completeness.

Identify potentially problematic data, make corrections, and eliminate the root cause of data problems.

Build replicable and efficient software code for data cleaning and estimation.

Design and customize reports based upon data in the database.

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.

Create documentation for all code.

What You’ll Bring

We are looking for a Research Data Analyst who brings strong statistical skills, technical precision, and careful judgment to work with considerable independence. You have deep experience in Stata, ideally three or more years, and you’re comfortable managing and analyzing large, complex datasets. You write efficient, replicable code, document it so others can follow it, and design code architectures that hold up as the data grows.

A master’s or doctoral degree and familiarity with advanced methods such as hierarchical linear modeling are a plus.

You have experience supporting quantitative social science research and know how to turn messy data into reliable evidence. You take ownership of the full data pipeline: extracting and cleaning data from state and federal sources, spotting problems and fixing their root causes, implementing new estimation methods, and producing charts, tables, and analyses ready for publication. You pay close attention to detail while keeping sight of the larger purpose behind the work: measuring educational opportunity in every community in America.

Experience with K-12 or postsecondary education data will help you contribute right away.

Strong collaborative instincts are equally important. You work closely with the Executive and Faculty Directors of the Educational Opportunity Project, communicate clearly about methods and findings, and know which questions you can resolve yourself and which need the team’s input. We value someone who serves as a dependable resource for non-routine requests, enjoys solving hard problems, and brings curiosity, persistence, and pride in producing rigorous, high-quality work.

Responsibilities

• 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.