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Voice of the Associate (VoA)

Students worked on text and data analysis through topic modeling with employee survey results using python for analysis and data visualization, based on country, region, functional area, the line of business, etc. Findings identified on which areas to focus or might need additional attention to help with risk prevention and mitigation.

  • Mentors: Hemen Patel
  • Students:
    • Felecia Liu, Aditi Kulkarni
    • Jenny Chen (LEAD), Rudy Winkler, Usama Saifi, Giang Le, Fiona Lee

Anomaly Detection 

  • Students supported the finance department focused on Travel and Expense (T&E). Objective was to predict any outliers of their offices’ expense reports (1.6 million records) and to data mine keywords that did not adhere to company policy. 
  • Students analyzed the significant deviations in the expenses (for ex. a meal for ~$4000, that hadn’t been accounted for) and also keywords within their parent expenses that did not fit with company policy. 
  • Students presented their findings which led BD to further explore ways to use sentiment analysis to predict any behavior that does not fit with their regulations and a dashboard to automate this. 
  • Mentor: Lilian Vinagre
  • Students: Aditi Kulkarni and Wanfei Luo