“Judicial V. Woodpecker” is looking for a new role as a Software Engineer or Data Scientist in San Francisco Bay Area.

A newly-minted M.S. in astrophysics, I am now exploring a career in data analytics/software development. During the past five years, I have written code to analyze image- and text-based data and high-dimensional models of galaxy clusters, primarily using Python (NumPy/SciPy). Teaching is a great love – over the past several summers, I have designed and directed project-based camps for students of all ages. Always eager to master new skills, I am especially interested in applying machine learning methods to build better data products for education, financial transactions, or image analysis.


  • Has 0 years experience in field
  • Most recent title is Graduate Research Assistant
  • Primarily works full-time roles
  • Recurse Center alum (https://www.recurse.com/)
  • Several years' experience teaching
  • Considers themselves a member of an underrepresented group

Notable Projects

  • Created a BFS-based web crawler to gather text data using the asyncio and Beautiful Soup Python libraries.
  • Built a toy content-based recommender system with the Pandas library. Used this project to enhance skills in software testing and design.
  • Visualized and analyzed high-dimensional simulated astronomical data sets, fitting models with Monte Carlo and gradient descent methods.

Ideal Company

I love building software and modeling data because these allow me to be continually learning. I value a company that works for its employees long-term professional growth. I want to be part of a team that encourages clean and communicative software design and testing. I learn best when I am talking with others about how to solve a problem, so I am looking for a company that emphasizes collaboration and mentorship. Work-life balance is important to me. While not strictly necessary, I would love to work for an organization whose product I believe is making the world better.


M.S. Physics, B.A. Physics


Python Data Analysis pandas