Intern Data Engineer | Argonne National Laboratory

The vehicle and mobility simulation group at Argonne National Laboratory has developed an exclusive large database of vehicles by collecting information from different sources. The group is currently looking to expand the list of vehicles through the development of further automated data collection processes, maintain the data through aggregation and integration of multiple databases, validate and cross-check the data entries by working on clustering algorithms and imputations methods. The entire workflow would require the student to be familiar with machine learning-based predictive modeling in high dimensional settings, a good understanding of time-dependent data, and a general fluency with all the data analysis tools.

Tasks overview:

1) Data analysis

2) Web-scraping and data integration

3) Data cleaning and imputation

4) Machine learning: time series analysis, clustering, predictive modeling.

Skills: A strong mathematical background, statistical analysis, machine learning.

Python, R, Matlab, Tableau, web-scraping tools, MongoDB, SQL.

Benefits: reimbursement of round-trip ticket to Chicago and visa expenses (note: due to covid19 working remotely might be necessary).

Duration: up to 6 months (full time). Work/Study setting could be considered for 20h/week afterwards.