Data Science Analyst

Data Science Analyst

The TMW Center for Early Learning + Public Health at the University of Chicago develops, tests, and implements evidence-based interventions designed to promote very young children's cognitive and social-emotional development, with a priority placed on that of children living in poverty. TMW Center interventions are designed to be overlaid onto existing health, education, and social service systems working at scale in a given community in order to meet families where they already are. Our goal is to effect population-level change in children's academic and developmental outcomes. To date, the TMW Center has three randomized controlled trial (RCTs) and an implementation study in active implementation, each amassing more data over time. In recent years the TMW Center's interventions and projects have become more complex and varied. These include launching an additional RCT, substantial piloting of new curricula, further analysis of its SPEAK scale, implementation of a broader messaging campaign, a community-wide demonstration project, and development of wearable technology, all of which have significantly increased the amount of data generated and needing to be analyzed. This increased volume of data and expanded lines of inquiry necessitate investment into the TMW Center's data systems and procedures to ensure the TMW Center can keep up with high quality and efficiency. To this end, we envision a Data Science Analyst role on the Research Analysis team that will further develop the TMW Center's data system and data organization processes and protocols to ensure consistency and quality, prepare for the large volume of anticipated incoming data, and produce quality, analyzable data sets. The ideal candidate is a detail-oriented thinker with experience in the organization and storage of data for research purposes and understanding of developmental and linguistic coding techniques. The TMW Center seeks candidates who are dynamic, collaborative, and curious.

Job Information

Data Science Analyst for Chicago, IL location. Develop and maintain all data storage/data management systems to ensure quality and completeness. Cleans, transforms, merges, and matches between large and complex research datasets using econometrics methods and causal inference techniques. Ensure secure data storage, guaranteeing regular backups and storage in compliance with HIPAA, current best practices, and study requirements. Develop pipelines, processes and protocols to automate or streamline the creation, cleaning, and preparation for analysis of data sets. Lead the research, development, planning, and execution of a comprehensive enterprise architecture for research in developmental psychology, linguistics and applied public health. Perform data analysis, insight synthesis, and presentation. Technological environment: Python; SQL; R; Tableau/STATA; data analysis, insight synthesis, and presentation; AWS; Hadoop/Spark/Dask; HPC; SQL Server.

Education

• Bachelor's degree in Information or Computer Science or related field plus 2 years of experience in data research required.

Required Skills

• 2 years experience with each: research techniques/methods including causal inference and econometrics; research in developmental psychology, linguistics or applied public health; Python; SQL; R; Tableau/STATA; data analysis, insight synthesis, and presentation; AWS; Hadoop/Spark/Dask; HPC; SQL Server. Asynchronous & live coding test required.

Working Conditions

• Background check with review of conviction history required. Four days in office required. $74,922/yr-$100,000/yr + benefits

Application Documents

• Resume (required)
• Cover Letter (required)

When applying, the document(s) MUST be uploaded via the My Experience page, in the section titled Application Documents of the application.

The University of Chicago offers a wide range of benefits programs and resources for eligible employees, including health, retirement, and paid time off.

The included pay rate or range represents the University's good faith estimate of the possible compensation offer for this role at the time of posting.