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Atharv P

- Research Program Mentor

MA at University of California Berkeley (UC Berkeley)

Expertise

Data Science

Bio

Hi! My name is Atharv Pathak and I am a recent graduate from UC Berkeley's Statistics department. From my past experiences, I have worked in data science/engineering related roles at State Farm, NASA and Micron Technology. These opportunities have really propelled my passion for data science and machine learning in all domains! I love ascertaining interesting research questions, wrangling and cleaning data and building models/solutions to derive key insights. A little bit about me: I love watching football and I am a huge Cincinnati Bengals fan (probably the only one from New Jersey). I also watch a lot of anime and love watching Demon Slayer, AOT and Spy Family. Lastly, I am an avid hip-hop head and I listen to a lot of underground music (Redveil, Jpegmafia, JID, Smino, Vince Staples, Saba, etc.)!

Project ideas

Project ideas are meant to help inspire student thinking about their own project. Students are in the driver seat of their research and are free to use any or none of the ideas shared by their mentors.

Chicago Food Health Inspection

For all the foodies out there, this is a great dataset to learn more about local and chain restaurants in Chicago. You can stratify the dataset and review inspection infractions based on your interests (like fast food chains). We can even feature engineer additional predictors to help predict whether or not a restaurant will have a violation. If you're not up for model building, we could even create an interactive dashboard solution to help visualize and better understand groups and patterns in the data. It really is all up to you! Dataset: https://data.cityofchicago.org/Health-Human-Services/Food-Inspections/4ijn-s7e5

Coding skills

Python, R

Teaching experience

In my undergrad, I have worked as a TA for STAT100 (Introduction to Statistics) and STAT200 (Data Science Exploration). I have had experience teaching non-technical, undergraduate students statistical and programming based concepts. In graduate school, I worked as a reader for PBHLTH245 (Multivariate Statistics), where I taught public health graduate students how to apply statistical methods in R on various health datasets.

Credentials

Work experience

Micron Technology (2023 - Current)
Data Scientist
NASA (2021 - 2022)
Data Science Intern
State Farm (2020 - 2021)
Data Engineering Intern

Education

University of Illinois at Urbana Champaign (UIUC)
BS Bachelor of Science (2021)
Aerospace Engineering and Statistics
University of California Berkeley (UC Berkeley)
MA Master of Arts (2022)
Statistics

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