Background

My name is Zachary Chipman, an aspiring data analyst with a Masters of Applied Data Science from Syracuse University and an Undergraduate degree from the University of Michigan. It was at an internship at the Lawrence Berkeley National Laboratory that I first gained an interest in data science. Although most of my work at the lab involved astronomy (my undergraduate field of study), I was surprised to find my advisor was involved in projects unrelated to astronomy. One such project was called FUEGO, where the goal was to use images and machine learning to detect wildfires across California. This project showed me that some of the skills I had learned could be applied to other fields. My goal is to develop my skills and design similar projects, making a positive impact in areas that are important to me, such as financial security and environmental awareness. To that end, I'm looking for an entry-level data analytics position at a company that shares my passion of using data to benefit others and will encourage continuous learning. Feel free to message/connect through LinkedIn if you would like to discuss any opportunities or anything else data science. You can also view my current/past projects on Github (https://github.com/ZChipman).

Job experience

• August 2018 - August 2019
  Intern
  Lawrence Berkeley National Laboratory
  

  Berkeley, CA, USA

  Interned under Dr. Carlton Pennypacker at the Lawrence Berkeley National Laboratory's Physics department. Worked on two projects:
  
  Used a remote telescope network to obtain photometric images on black-hole/star pair, Cygnus X-1, and used Python to observe its orbital period.
  
  Assisted on a machine learning project known as FUEGO, with the goal of using images of smoke to speed up wildfire detection across California. My main contribution was cleaning up the training images to improve the model’s accuracy.

Education

• Syracuse University
  MS in Applied Data Science
  

  2021 - 2022

  Graduated with a Masters of Applied Data Science, focusing on Business Analytics and Data Analytics/Machine Learning. Gained experience and demonstrated proficiency of the program's Learning Goals:
  
  1. Describe a broad overview of the major practices in data science.
  2. Collect and organize data.
  3. Identify patterns in data via visualization, statistical analysis, and data mining.
  4. Develop alternative strategies based on the data.
  5. Develop a plan of action to implement the business decisions derived from the analysis.
  6. Demonstrate communication skills regarding data and its analysis for managers, IT professionals, programmers, statisticians, and other relevant professionals in their organization.
  7. Synthesize the ethical dimensions of data science (e.g., privacy).
• University of Michigan
  BS in Astronomy/Astrophysics
  

  2014 - 2018