Predoctoral Scholar - Machine Learning Data Scientist - JR27067-3800

University of Chicago - Chicago, IL

Full-time - Entry Level

Chicago, IL

Educational Services

About the position

The University of Chicago's Harris School of Public Policy is seeking a Predoctoral Scholar in Machine Learning Data Science for a one-year Research Professional position. The role focuses on education research and involves working under the supervision of Professor Anjali Adukia. The successful candidate will engage in data collection, transformation, and analysis, utilizing machine learning and natural language processing techniques to support various research applications.

Responsibilities

• 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 use version control on GitHub, including communicating and documenting your process to other researchers on the project.
• Work collaboratively with a team of researchers.
• Assist in analyzing data for the purpose of extracting applicable information and perform research projects that provide analysis for various 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.
• Perform other related work as needed.

Requirements

• Minimum requirements include a college or university degree in a related field.
• Knowledge and skills developed through relevant experience.

Nice-to-haves

• Bachelor's Degree in Economics, Statistics or related disciplines.
• Previous research experience.
• 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.

Benefits

• Collaborative work environment with a focus on social change and policy impact.