Currently a third-year Data Science student at the California Institute of Technology with an interest in prediction. I was in the Applied Physics option before Data Science was released.
I have always wanted to be a wizard, and there are several things I expect a wizard to know about tomorrow:
- the financial markets,
- college admissions and human nature,
- the weather.
The first task seems to be the most reasonable career choice at the moment, so I am looking for a full-time job (2020) in that field. I have done similar work in the past and found strategy design and backtesting to be quite enjoyable. Other interesting applications of predictive analysis and machine learning also appeal to me. Money aside, uncovering human nature is the highest priority.
Places I have been in the past:
- System Test internship at MemVerge (2018)
- Quantitative tactics internship at SBB Research Group (2018)
- Summer Research Fellowship at Caltech's plasma lab, investigating dusty plasmas with a strobe lamp and lasers (2017)
- Quantitative research internship at QTG Capital (2016)
- Garcia research internship at Stony Brook for materials science: nanoparticle synthesis and characterization for hydrogen fuel cells (2015)
- UConn Physics department for a project relating dwarf galaxies to open clusters in the Milky Way (2014)
- "Reinforcement Learning for Portfolio Optimization"
- "Prediction of Graduate School Application Results with Sentiment Analysis and SVM"
- Neural networks and multivariate regression to analyze car-sharing services
- Determining the Molecular Weight of Polystyrene in Food-Serving Plates by Thin Film Analysis
- A Mechanical Analogy to Adaptive Optics: The Automatic Ping-pong Bouncer
- Caltech CS155 Kaggle 2019, Rank 1 (solo) of 80 teams: "Voter Turnout Prediction in 2008 Elections"
- Caltech CS155 Kaggle 2018, Rank 2 (solo) of 74 teams: "ML Sentiment Analysis of Amazon Reviews"
- Chicago Quantitative Alliance Investment Challenge 2017-2018, Rank 20 of 101
- Citadel/Citadel Securities SoCal Data Open 2017
- Moody’s Math Modelling Challenge 2016, Top 80 of 1084
I code most fluently in:
- Python (machine learning / quant things)
- R (some quant things / data aggregation)
- Mathematica (physics homework)
- \(\LaTeX\) (reports and papers)
Why did you switch from Physics to Data Science? I get only one shot at life. I don't think I would survive in academia, as my patience is limited and Physics is not an easy field to do well in. Some parts of physics truly interest me, but predicting the future was a main motivation for studying it, and data science is a more direct path to that.
Why are you interested in [our company]? If I sent in my resume, I must believe that your company is up to something interesting :)