Job Description:

• Collect, transform, and process raw and unstructured data into a usable data science format.

• Develop classification models using supervised and unsupervised machine learning/deep learning techniques for various research applications.

• Design and implement NLP algorithms and techniques for text preprocessing, feature extraction, sentiment analysis, semantic role labeling, and document classification.

• Visualize complex data for inclusion in manuscripts and presentations.

• Write documentation and using version control on GitHub, including communicating and documenting your process to other researchers on the project.

• Work collaboratively with a team of researchers.

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

• May assist staff or faculty members with data manipulation, statistical applications, programming, analysis and modeling on a scheduled or ad-hoc basis.

• Performs other related work as needed.

Preferred Qualifications

Education:

• Bachelorâ™s Degree in Economics, Statistics or related disciplines.

Experience:

• Previous research experience.

Technical Skills or Knowledge:

• Proficiency in Stata; ability to use other statistical software packages (e.g., R, Python, or BASH).

• Significant coursework or experience in data analysis.

• Exceptional technical skills and a proven ability to creatively tackle difficult empirical problems.

Preferred Competencies

• Proven ability to work effectively in small teams, demonstrating a strong desire to both learn from and mentor other team members.

• Excellent oral and written communication skills.

• High attention to detail and quality in data analysis and written material.

• Experience with or proficiency in R, Python, and Bash scripting.

• Experience with NLP techniques such as word and document embeddings.

• Experience using clustering and dimensionality reduction techniques such as K-means and PCA

• Experience implementing Neural Networks using Tensorflow, PyTorch, Scikit-Learn, OpenCV, deep learning, and other artificial intelligence techniques.

• Experience with image classification/recognition and tools to analyze illustrations in addition to photographs.

• Familiarity with Linux, UNIX, and High Performance Computing environment.

• Experiencing forming and testing hypotheses.

• Drive to learn new programming or data analysis techniques.

• Strong communication skills and the ability to break down complex technical problems.

• Significant knowledge of statistics and/or empirical economics research.

• Demonstrated ability to review and prioritize work independently and effectively.

• Demonstrated ability to be resourceful and creative in problem-solving.

Working Conditions

• Predoctoral Scholar will be based out of Chicago, IL.

Application Documents

• Resume (required)

• Cover Letter (preferred)

• References (preferred)

The University of Chicago is an Affirmative Action/Equal Opportunity/Disabled/Veterans Employer and does not discriminate on the basis of race, color, religion, sex, sexual orientation, gender identity, national or ethnic origin, age, status as an individual with a disability, protected 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 the Applicant Inquiry Form.

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About University of Chicago (UC)

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