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Data Science Awards

External Awards

MinneAnalytics Scholarship

MinneAnalytics offers scholarships to undergraduate students who display a passion for pursuing a career in analytics and a commitment to engaging with the community. Each year the Department of Statistics and Data Science applies for an award and nominates a student from the Department who displays a passion for pursuing a career directly related to data science and analytics and has an ongoing commitment to community engagement.

2021 MinneAnalytics Scholarship Recipients

2021 recipients Kylie Lin and Andrew Rowan

Kylie Lin
Majors: Communication Studies, Cognitive Science
Minor: Data Science

Kylie is a junior at Northwestern University pursuing a double major in Communication Studies and Cognitive Science along with a minor in Data Science. Through her statistics coursework, she became interested in both creating and understanding data visualizations. This led her to the Visual Thinking Lab at Northwestern where she currently conducts research examining how people interpret information from data visualizations, and in the past she has contributed publishing a paper to IEEE VIS. In the future, she hopes to continue to conduct visualization research by applying to Master's or PhD programs in Information Management.


Andrew Rowan
Major: Journalism
Minors: Data Science and Business Institutions 

Andrew Rowan is a junior at Northwestern University studying journalism, data science, and business institutions. He currently serves as news director, executive producer, and reporter for the Northwestern News Network, the campus broadcast station. Previously, Andrew has served as a production intern for NBC News Now and a social media intern for MSNBC.  

 Read more about the MinneAnalytics Scholarship winners here


2020 MinneAnalytics Scholarship Recipient

Avriana Allen
Majors: Statistics; Journalism
Minors: Creative Writing
Read more about Avriana and the MinneAnalytics Scholarship here


Internal Awards

Department of Statistics and Data Science Data Science Competition 2020

Six students in Northwestern’s data science minor emerged as winners of the Department’s data competitions in spring 2020. The competitions, which take place as part of the departments data science course sequence, challenge students to build accurate predictive models. This year’s winners include students majoring in statistics, as well as in related fields such as engineering and economics.

Students participated in two competitions in 2020 where they attempted to forecast risks and earnings based on information in loan applications. The first competition, in which required students to predict whether a large amount of the principal of a loan was ever repaid, featured the following top three finishers:

  1. Peiwen Ren is a junior majoring in Materials Science and a minor in Data Science and International Studies. Peiwen used a random forest model that regularized tree depth. When he graduates in 2021, he plans to work in material informatics.
  2. Chirag Akella is a junior majoring in Statistics and Data Science and minoring in Economics. Chirag used a random forest he tuned using Northwestern’s Quest Computing Cluster. When he graduates in 2021, he hopes to apply his data science skills to derive actionable insights from big and noisy data.
  3. Jay Patel is a junior majoring in Economics and minoring in Data Sciences with a Managerial Analytics Certificate. Jay tuned a random forest that restricted the set of features about the loan applications used to make predictions. When he graduates in 2021, he plans to work in the consulting industry.

The second competition found students predicting the total losses or earnings on a loan. The top three finishers were:

  1. Junhua Tan is a junior majoring in Neuroscience and minoring in Computer Science and Data Science. Junhua tuned a gradient boosted model for this competition. Junhua plans to pursue a career in data science after graduating in 2021.
  2. Avriana Allen, junior majoring in Journalism and Statistics and minoring in Creative Writing. Avriana used a thoroughly tuned random forest model for her competition entry, which was no small feat given the size of the datasets involved in the competition. When she graduates, the plans to pursue a career at the intersection of journalism, technology, and data.
  3. Kevin Zhang, junior majoring in Statistics and minoring in Computer Science. Kevin used a clever feature extraction approach coupled with a well-tuned gradient boosted model. When he graduates in 2021, he wants to work in data science with an emphasis in web development and artificial intelligence.