Associate Data Scientist

Department

UL Crime Ed Lab Data Science

About the Department

Who We Are
In cities across the country, people face high rates of gun violence, under-resourced schools, and social harms associated with the criminal justice system -- all of which disproportionately impact people of color. These inequalities have profound consequences on public safety and opportunity. As a society we have failed to address these challenges, in part, because of our lack of understanding of the most effective and cost-effective solutions that can have a real impact on people’s lives. We believe that rigorous research can help.

The University of Chicago Crime Lab and Education Lab partner with cities and communities to use data and rigorous research to design, test, and scale programs and policies that enhance public safety, improve educational outcomes, and advance justice. Our mission is to combine world-class data science and research, in partnership with government agencies, to substantially improve the effectiveness of the public sector and achieve impact at scale.

The Role
The University of Chicago Crime Lab and Education Lab are seeking an Associate Data Scientist to work on our portfolio of projects applying machine learning to public policy. We’re seeking a smart, motivated, and detail-oriented person to work on all parts of our applied machine learning projects – all the way from cleaning and structuring raw data to developing predictive models and evaluating them in a randomized control trial. An ideal candidate will have experience in applying principals of machine learning to real-world data and supporting analytics research work.
The position offers the opportunity to work directly with leading researchers at the University of Chicago and policymakers on projects with immediate real-world impact. You will collaborate closely with PhD-level computer science and economics researchers, as well as top-notch research managers and organizational leadership. This position is particularly well-suited for candidates who may be interested in pursuing a PhD in the future or for data scientists who want to transition from industry to public policy research.

Job Summary

The job performs routine assignments related to scientific research projects. Ensures compliance of research activities with institutional, state, and federal regulatory policies, procedures, directives and mandates. Analyzes possible solutions using standard procedures. Writes articles, reports and manuscripts. Assists in drafting presentations on research findings.

Responsibilities

• Contributes to the implementation, and validation of an efficient and reproducible data processing pipeline.

• Assists in building and evaluating statistical models using best practices of machine learning and statistical inference.

• Drafts project memos, summaries, presentations, reports, and other work products for dissemination targeting both policymakers, academic researchers, and other stakeholders, as needed.

• Assists in analyzing data for the purpose of extracting applicable information. Performs research projects that provide analysis for a number of programs and initiatives.

• 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 request and engages other IT resources as needed.

• Performs other related work as needed.

Minimum Qualifications

Education:

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

Work Experience:

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

Certifications:

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Preferred Qualifications

Education:

• Bachelor's degree in computer science, statistics, data science, economics, or a closely related field.

Experience:

• Proficiency with statistical data analysis and machine learning using Python or R. Ability to work in both is strongly preferred.

Preferred Competencies

• Knowledge of machine learning techniques and algorithms.

• Experience developing reproducible and maintainable code.

• Good written and verbal communication skills, with the ability to present data in a simple and straightforward way for non-technical audiences.

• Strong interpersonal skills.

• Strong initiative and a resourceful approach to problem solving and learning.

• Ability to work independently and as p