Staff Data Engineer
Hyde Park Campus
University of Chicago
One of the world’s leading research universities, the University of Chicago inspires scholars to pursue field-defining research, while providing a transformative education for students.Department
About the Department
Job Summary
Responsibilities
Consult with 11th Hour grantees, to clarify goals, identify collaboration opportunities and support data collection and modeling.
Write high quality code (Python, JS) using modern dev ops tools (docker, etc.).
Develop workshops and trainings to build 11th Hour program staff and grantee data capacity.
Review and evaluate potential joint 11th Hour-UChicago Data Science Institute projects for technical merit and feasibility.
Develop open source data science resources to support the data literacy and capacity for environmental nonprofits and companies to use.
Conduct an independent research program in the SDE area of specialty as well as disseminate and publish these results.
Engage with other research initiatives at the UChicago Data Science Institute including establishing external collaborations outside of the SDE area of expertise.
Support the ongoing education, training and consulting programs at the UChicago Data Science Institute.
Mentor and support graduate and undergraduate students in the UChicago Data Science Clinic.
Grant writing activities to support ongoing initiatives in data science.
Contribute to the life of the UChicago Data Science Institute environment through service and participation in UChicago Data Science Institute activities, including public lectures, blog posts, contributing to open source technologies, etc.
Develop materials communicating significant results, best practices and case studies with specific technologies, and documentation for significant software.
Has a deep understanding of methods to analyze complex data sets for the purpose of extracting and purposefully using applicable information. May develop and maintain infrastructure that connects data sets.
Designs and evaluates statistical models and reproducible data processing pipelines using expertise of best practices in machine learning and statistical inference. Provides expertise for high level or complex data-related requests and engages other IT resources as needed. Partners with other campus teams to assist faculty with data science related needs.
Performs other related work as needed.
Minimum Qualifications
Education:
Minimum requirements include a college or university degree in related field.---
Work Experience:
---
Certifications:
---
Preferred Qualifications
Education:
Graduate degree, preferably in computer science, data science, statistics, mathematics, engineering or related computational field.
Experience:
At least three (3) years of professional experience writing code in an interpreted language, such as Python or Javascript.
Experience communicating results through writing and presentations, both in and out of one’s own discipline.
Knowledge of software development best practices and commonly used tools.
Demonstrated experience in software engineering, applied machine learning and/or advanced statistical methods.
Demonstrated record of success working at the intersection of environment, human rights and data science.
Experience participating in open source software development and significant contributions to open source projects are also highly valued in this role.
Working Conditions
Office environment.
Hybrid schedule with two days a week work from home and three days in the office.
Application Documents
Resume (required)
Cover Letter (preferred)
When applying, the document(s) MUST be uploaded via the My Experience page, in the section titled Application Documents of the application.
Job Family
Role Impact
FLSA Status
Pay Frequency
Scheduled Weekly Hours
Benefits Eligible
Drug Test Required
Health Screen Required
Motor Vehicle Record Inquiry Required
Posting Statement
The University of Chicago is an Affirmative Action/Equal Opportunity/Disabled/Veterans and does not discriminate on the basis of race, color, religion, sex, sexual orientation, gender, gender identity, national or ethnic origin, age, status as an individual with a disability, military or veteran status, genetic information, or other protected classes under the law. For additional information please see the University's Notice of Nondiscrimination.
Staff Job seekers in need of a reasonable accommodation to complete the application process should call 773-702-5800 or submit a request via Applicant Inquiry Form.
We seek a diverse pool of applicants who wish to join an academic community that places the highest value on rigorous inquiry and encourages a diversity of perspectives, experiences, groups of individuals, and ideas to inform and stimulate intellectual challenge, engagement, and exchange.
All offers of employment are contingent upon a background check that includes a review of conviction history. A conviction does not automatically preclude University employment. Rather, the University considers conviction information on a case-by-case basis and assesses the nature of the offense, the circumstances surrounding it, the proximity in time of the conviction, and its relevance to the position.
The University of Chicago's Annual Security & Fire Safety Report (Report) provides information about University offices and programs that provide safety support, crime and fire statistics, emergency response and communications plans, and other policies and information. The Report can be accessed online at: http://securityreport.uchicago.edu. Paper copies of the Report are available, upon request, from the University of Chicago Police Department, 850 E. 61st Street, Chicago, IL 60637.
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: Computer Science Consulting Data pipelines Deep Learning Docker Engineering JavaScript Machine Learning Mathematics NLP Open Source Pipelines Python Research Security Statistics
Perks/benefits: Career development Health care
More jobs like this
Explore more career opportunities
Find even more open roles below ordered by popularity of job title or skills/products/technologies used.