Job Description

Department
 

BSD E&E - Administration

About the Department
 

The Bettencourt Laboratory in the Department of Ecology and Evolution at The University of Chicago is seeking a Data Scientist Analyst. In the Betterncourt Lab much of the research and service are presently dedicated to the scientific study of cities and associated practices to help make our societies more just and sustainable. The guiding vision is to approach cities with epistemic humility towards a complex and multi-faceted phenomenon involving the lives of billions of people, deserving to be appreciated and understood. A number of recent discoveries show that cities are a natural phenomenon with predictable properties and dynamics and reveal associated processes of natural design. They explain how cities can naturally enable open-ended human collaboration and invention while improving access to basic services, education, health, and political participation. New forms of practice and policy are emerging from these insights, supporting human agency across scales, collaborative institutions, novel approaches to design, and new uses of technology for sustainability and human development.

Job Summary
 

The Bettencourt Laboratory in the Department of Ecology and Evolution at the University of Chicago is seeking a Data Scientist to work primarily on the Million Neighborhoods Project, which is a large-scale computational approach to mapping and analyzing worldwide built environments using building footprints, road networks, and other spatial data.

Responsibilities

• Curates and updates continental-scale geospatial data.
• Runs high-performance code and data analysis.
• Assists in analyzing data for the purpose of extracting applicable information. Performs research projects that provide analysis for a number of programs and initiatives.
• Helps prepare results for publication, grants, and online visualizations and presentations.
• May assist staff or faculty members with data manipulation, statistical applications, programming, analysis and modeling on a scheduled or ad-hoc basis.
• Collects, organizes, and may analyze information from the University's various internal data systems as well as from external sources.
• Maintains and analyzes statistical models using general knowledge of best practices in machine learning and statistical inference. Performs maintenance on large and complex research and administrative datasets. Responds to requests and engages other IT resources as needed.
• Analyzes moderately complex data sets for the purpose of extracting and purposefully using applicable information.
• Cleans, transforms, merges, and matches between large and complex research and administrative datasets. Plans own resources to collect, organize, and analyze information from the University's various internal data systems as well as from external sources.
• Performs other related work as needed.

Minimum Qualifications
 

Education:

Minimum requirements include a college or university degree in related field.

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Work Experience:

Minimum requirements include knowledge and skills developed through 2-5 years of work experience in a related job discipline.

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Certifications:

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Preferred Qualifications

Education:

• Masters degree in engineering or biomedical engineering

Technical Skills or Knowledge:

• Proficient with Python, Git SQL, C/C ++, Matlab, and Lua.
• Skilled in setting up statistical process control.
• Skilled at training colleagues in using internal SQL-based software tools.

Preferred Competencies

• Excellent verbal and written communication skills.
• Work successfully with university students, faculty, and staff.
• Multi-task and manage multiple responsibilities simultaneously.
• Attention to detail.
• Excellent interpersonal skills.
• Flexible and perform new tasks with short notice.
• Display a professional, calm, and courteous demeanor and maintain when under pressure.
• Follow an issue through to resolution.
• Work under minimal supervision and oversight.

Application Documents

• Resume/CV (required)
• Cover Letter (preferred)
• References Contact Information (3)(preferred)

Job Family
 

Research

Role Impact
 

Individual Contributor

FLSA Status
 

Exempt

Pay Frequency
 

Monthly

Scheduled Weekly Hours
 

40

Benefits Eligible
 

Yes

Drug Test Required
 

No

Health Screen Required
 

No

Motor Vehicle Record Inquiry Required
 

No

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.