1) The Data Scientist will assist faculty, research professionals and PhD students with the use of technology in instruction and research, including but not limited to large data manipulation and management, complex statistical analysis and modeling, data mining and other research methodologies.
2) Work with researchers to apply advanced analytical techniques to extract, manipulate, and analyze large volumes of financial, economic and marketing data.
3) Consults with faculty on technology requests to support research and teaching.
4) Assists faculty members with large data manipulation, complex statistical applications, programming, analysis and modeling.
5) Consults with faculty, research professionals and PhD students on high performance computing (HPC), including optimizing and parallelizing code and leveraging GPU resources.
6) Co-manages software and configurations on Boothâ™s Linux HPC cluster.
7) Serves as primary contact point for all faculty research technology requests and engages other IT resources to assist as needed.
8) Consults with faculty on requests for research data; investigates data options from multiple sources to support faculty teaching and research.
9) Partners with other University of Chicago campus teams, including the Research Computing Center, Computation Institute and Globus to assist faculty with research technology challenges.
1) Expert level knowledge and at least three years of experience with statistical programming, data querying and manipulation within statistical software packages such as R, Python, Matlab, Stata or SAS.
2) Manage multiple projects simultaneously in a fast-paced environment with strong attention to detail and accuracy.
3) Proven ability to work independently as well as on a team.
4) Strong written and verbal communication skills.
5) Superior quantitative abilities, logical reasoning and analytical skills required along with a high level of attention to detail.
6) Effective at working and communicating with both faculty and Information Technology staff.
7) Expert level knowledge of the extraction, transformation, loading and manipulation of large data and databases (e.g. multi-terabyte files).
8) Knowledge of, or familiarity with, scripting languages such as Bash, Perl, Python and PowerShell or other comparable programming skills.
9) Familiarity with SQL and/or other methods of accessing data in relational databases, such as Microsoft SQL Server, MySQL or PostgreSQL.
10) Ability to use Microsoft Excel, SQL and Tableau programming skills for data mining and to supplement and enhance data analysis and visualization.
11) Demonstrated working knowledge of big data technologies (Spark, Hadoop) including HDFS, JobTracker, MapReduce, Hive, Pig, Yarn and Mahout.
12) Motivation to independently explore new computational tools and techniques to improve research.
1) Master's degree.
2) Ph.D. degree.
1) At least three years of professional work or comparable academic experience.
2) Experience with Linux-based grid/cluster computing.
3) Experience using multiple operating systems (Windows, Linux, macOS).
4) Experience and familiarity with how to optimize code to run in parallel environments, including those that leverage GPUs.
5) Experience working as a research professional or data analyst in the finance, economics or marketing industries.
6) Experience transforming and connecting isolated data files and databases into shared data assets that can easily be accessed and used by many researchers.
2) Cover letter
NOTE: When applying, all required documents MUST be uploaded under the Resume/CV section of the application.
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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
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