About Me

I'm an Operations Research/Computer Science undergraduate at Cornell University. Operations Research (OR) is a discipline that pertains to obtaining optimal or near-optimal solutions for complex decision-making problems. It draws upon fields such as mathematical modeling and optimization, statistical analysis, computer science, and psychology.

As a Go player, the shocking success of AlphaGo inadvertently dragged me into the world of machine learning and artificial intelligence. I enjoy learning about the field and have done a couple of projects in my free time, including a few Kaggle-style competitions. I also write about ML on Quora.

I also love keeping up and tinkering with the latest technologies. I've recently spent some time playing around with cloud services, mainly architecting and building Big Data/ML solutions on AWS and GCP.

When I'm not studying or working, you can find me playing tennis, running, cooking, playing poker or Go, writing, reading, and occasionally, competing in a Spartan Race.

Contact Details

Maverick Lin


Cornell University

B.S. in Operations Research and Information Engineering May 2019
Minor in Computer Science

Relevant Courses: Algorithms, Machine Learning, Data Mining, Stochastic Processes, Probability & Statistics, Optimization, Natural Language Processing, Linear Algebra, Differential Equations, Multivariable Calculus


Goldman Sachs

Digital Innovators Program Sep 2019 - Present

Hudson Data

Data Scientist June 2019 - Sep 2017

- Consulted for a Fortune 500 company to improve existing fraud detection models
- Leveraged PySpark and Apache Hive to analyze millions of credit card transactions (totaling over $14B) and perform feature engineering
- Implemented distributed version of RuleFit in PySpark to increase model interpretability
- Worked on graph-based algorithm for automatic detection of Points-of-Compromises (POCs)

Chardan Capital Markets

Investment Banking Summer Analyst June 2017 - Aug 2017

- Conducted preliminary M&A Researchfor $1.2B Healthcare Client
- Analyzed hundreds of equity reports, SEC filings, and press releases to identify underlying drivers of major stock movements for 20+ biotechnology companies
- Worked with senior management to prepare valuation of Amazon using public company comparable and sum-of-parts valuation; analysis showed company was under-valued by 70% (massive upside from AWS segment)
- Worked with head of research to build linear regression models to predict companies’ market cap given the type and number of FDA/EMA designations received; models showed that the FDA Breakthrough Therapy Designation (BTD) and EMA Priority Medicine (PRIME) proved to be significant feature variables


Languages: Python (scikit-learn, numpy, pandas, keras/tensorflow), Java, R, SQL
Machine Learning: Logistic/Linear Regression, Ensemble Models, Deep Learning
Cloud Computing: AWS Platform, Google Cloud Platform
Big Data: Hadoop, Spark
Other Tools: Web Scraping (BeautifulSoup, Seleniumm, HTML, CSS), Git, LaTeX


AWS Certified Developer (Associate)


Academic: Dean's List (2016, 2019)
Quora: 2018 Top Writer
Tennis: Cornell Men's Varsity Tennis (2015-2017), 2017 Ivy League Champions,
Five-Star Recruit, NJ State Champion (2013)
Go: 5 Dan Player, Cornell Go Club, US National Go Championship Runner-Up (2008)
Spartan Races: 1 Spartan Sprint
Author: Cracking the Data Science Interview

Get In Touch.

If you have a project that you think I can help with, or just want to say hello, then feel free to get in touch! Cheers.

Message Me