1) The Data Scientist will assist Chicago Booth with the use of technology in research, including but not limited to large data manipulation and management, complex statistical analysis and modeling, data mining and other research methodologies. Work with Institutional research and strategic insights team, the Deansâ™ office, and Boothâ™s leadership group to apply advanced analytical techniques to extract, manipulate, and analyze large volumes of data pertaining to different aspects of the schoolâ™s life. 2) Translates advanced business analytics problems into technical approaches that yield actionable recommendations in diverse areas across Booth.
3) Consults Institutional Research and Strategic Insights team on technology requests to support research and teaching across Booth.
4) Works in multi-disciplinary and cross-functional spaces to translate business requirements into artificial intelligence goals and modeling approaches; rapidly iterate models and results to refine and validate approach.
5) Works in a dynamic environment with virtual and face-to-face interactions. Utilize structured approaches to solving problems, managing risks, and documenting assumptions while communicating results and educating others through insightful visualizations, reports, and presentations.
6) Assists with large data manipulation, complex statistical applications, programming, analysis and modeling; Analyzes and models structured and unstructured data and implement algorithms to support analysis using advanced statistical and mathematical methods from statistics, machine learning, data mining, econometrics, and operations research.
7) Consults with the Institutional Research and Strategic Insights team and analysts across Booth on grid/cluster computing, including optimizing and parallelizing code and leveraging GPU resources when applicable.
8) Consults with the Deansâ™ Office, Boothâ™s leadership group and other analysts across Booth on research requests. Researches data options from multiple sources to support research across Booth.
9) Partners with other Booth teams, such as Booth IT and University of Chicago campus teams, including the Research Computing Center, Computation Institute and Globus to assist the school with technology research challenges.
1) Expert level knowledge and at least three years of experience with of statistical programming, data querying and manipulation data within statistical software packages such as SAS, Matlab, Stata, R or other comparable tool.
2) Ability to 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) Excellent problem-solving skills, verbal/written communication, and ability to explain technical concepts to business audience.
5) Ability to apply artificial intelligence techniques to achieve concrete business goals while working with the stakeholders to understand available resources and constraints around data (sources, integrity, and definitions), processing platforms, and security. Superior quantitative abilities, logical reasoning and analytical skills required along with a high level of attention to detail.
6) Skill working and communicating with the Deans, faculty and senior leadership and Information Technology staff.
7) Familiarity with how to optimize code to run in parallel environments, including those that leverage GPUs.
8) Expert level knowledge of the extraction, transformation, loading and manipulation of large data and databases (e.g. multi-terabyte files).
9) Knowledge of or familiarity with scripting languages such as Perl, Python and PowerShell or other comparable programming skills.
10) Familiarity with SQL and/or other methods of accessing data in relational databases, such as Oracle, and Microsoft SQL Server.
11) Familiarity with emerging Cloud Capabilities on Azure, GCP and/or AWS; Experience with command-line scripting, data structures, and algorithms.
12) Ability to use Microsoft Excel, SQL and Tableau programming skills for data mining and to supplement and enhance data analyses.
13) Demonstrated working knowledge of Hadoop technologies including HDFS, JobTracker, MapReduce, Hive, Pig, Yarn and Mahout.
1) Master's degree in computer science, engineering or related fields.
1) At least three years of professional work or comparable academic experience.
2) Experience working as a research assistant or data analyst in higher education industry.
3) Experience transforming and connecting isolated data files and databases into shared data assets that can easily be accessed and used by many researchers.
4) Experience with grid/cluster computing.
2) Cover letter
NOTE: When applying, all required documents MUST be uploaded under the Resume/CV section of the application.
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