EOP Data Analyst - California, United States - Stanford University

Description

The Educational Opportunity Project (EOP) at Stanford University is working toward a future where all children have access to equitable educational opportunities.

We are measuring educational opportunity in every community in America and have built the most comprehensive national database of academic performance in the U.S., based on over 500 million test scores.

We hope that researchers will use the data to generate evidence about what policies and contexts are most effective at increasing educational opportunity, and that such evidence will inform educational policy and practices.

We seek an equity-minded, quantitative specialist to join our team as an

Educational Opportunity Project Data Analyst .

The EOP Data Analyst will develop, implement, and maintain strong data management systems critical to the success of the Educational Opportunity Project.

This includes preparing datasets for future public releases of SEDA on our website; cleaning, organizing, and harmonizing data from large longitudinal education datasets, including ED Facts , the Common Core of Data, Civil Rights Data Collection, among others; and supporting the development of research publications and reports for partners in the field (i.e., school districts and state departments of education).

The ideal candidate is highly analytical, self-motivated, innovative, and a skilled communicator with a passion for using data to study educational opportunity.

Experience using Stata and a strong statistical background (understanding of statistical modeling and practice developing, interpreting, and presenting analyses and research) is

required

for this role.

Note:
This position is a 1-year fixed term appointment that may be renewed based on performance and funding.

You will be offered a hybrid schedule, in which you will be required to be onsite at least 3 days per week

.

Interested applicants should submit a resume and a cover letter describing why they are interested in this position at this stage of their career.

Candidates must be eligible to work in the US. Visa sponsorship is not available for this position.

This is an exciting and dynamic time for the EOP as we create an innovative path to impacting the educational opportunity gap.

It is also an exciting time for the Stanford Graduate School of Education where many new research programs are beginning, and faculty searches are underway for the very best in their fields.

The EOP Data Analyst will play a key role in expanding our project's capacity to achieve our mission. This position will be supervised by Dr. Erin Fahle, Executive Director of the EOP, and Dr. Sean Reardon, Faculty Director of the EOP. The analyst will also collaborate closely with other faculty, students, and research staff affiliated with the EOP.

Who We Are:
The Educational Opportunity Project is based at the Stanford University

Graduate School of Education (GSE)

, which 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, 250 staff, 14,000 alumni and countless people from the local and global communities we work with and impact. The work environment is dynamic, deadline-driven, fast-paced, and energetic. Please visit

for more information about our work and team.

What You'll Do:
As a data analyst, you

will develop, implement, and maintain strong data management systems critical to the success of the EOP.

This includes writing Stata code to clean and construct complex datasets, drafting technical documentation, and performing statistical analyses aligned with the EOP team's research plan.

You will work closely with the broader EOP research team.

Your primary responsibilities will include:

We are looking for someone who has demonstrated experience in quantitative data management and Stata programming and who is dedicated to the EOP mission of conducting research to help ensure that all students have equal educational opportunities.

This role requires strong programming skills, effective time and priority management, and an ability to work independently. A good sense of humor is appreciated (where appropriate) and a strong, dedicated work ethic is a must.
Cleaning, optimizing, and maintaining existing SEDA code and datasets, including producing written documentation of your process and decisions.
Programming , testing, and integrating new code into the SEDA code architecture.
Writing efficient code to implement complex statistical procedures under the guidance of senior staff.
Developing data extracts, reports, memos, charts, graphs, and tables for use by researchers and for publication and presentation.
Communicating with various stakeholders to answer and document specific questions about datasets, primarily the SEDA dataset.
Collaborating with EOP faculty, data analysts, and graduate and undergraduate student research assistants on various projects.
To be successful in this position, you will bring:
Bachelor's degree or a combination of education and relevant experience. Experience in a quantitative discipline such as economics, or statistics.
Substantial experience with MS Office and analytical programs.
Strong writing and analytical skills.
Ability to prioritize workload.

In addition, preferred qualifications include:
Proficiency and substantial experience using Stata statistical software, including the Mata programming language.
Experience working with large datasets and familiarity with data organization (e.g., data structures, record layouts, and file structures).
Experience planning and executing quality assurance/data validation systems for large data sets.
Familiarity with advanced statistical methods (e.g., hierarchical linear modeling).
Demonstrated knowledge or interest in education research.
Background in statistical modeling and experience developing, interpreting, and presenting analyses and research.
Prior coursework or experience using hierarchical linear modeling (HLM) or multilevel modeling.
The expected pay range for this position is $85,000 to $105,000 per annum.

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 (

) 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.

Why Stanford is for You:
Imagine a world without search engines or social platforms. Consider lives saved through first-ever organ transplants and research to cure illnesses. Stanford University has revolutionized the way we live and enrich the world. Supporting this mission is our diverse and dedicated 17,000 staff. We seek talent driven to impact the future of our legacy. Our

culture

and

unique perks


empower you with:
Freedom to grow. We offer career development programs, tuition reimbursement, and course auditing. Join a TedTalk, film screening, or listen to a renowned author or global leader speak.
A caring culture. We provide superb retirement plans, generous time-off, and family care resources.
A healthier you. Climb our rock wall or choose from hundreds of health or fitness classes at our world-class exercise facilities. We also provide excellent health care benefits.
Discovery and fun. Stroll through historic sculptures, trails, and museums.
Enviable resources. Enjoy free commuter programs, ridesharing incentives, discounts and more

How to Apply:
We invite you to apply for this position by clicking on the "Apply for Job" button. To be considered, you must submit a cover letter and résumé along with your online application.
Finalists must successfully complete a background check prior to working at Stanford University.

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 accommodations to applicants and employees with disabilities. Applicants requiring a reasonable accommodation for any part of the application or hiring process should contact Stanford University Human Resources at

. For all other inquiries, please submit a

contact form

.

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.

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Graduate School of Education, Stanford, California, United States
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Graduate School of Education, Stanford, California, United States
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