Jun 2021 – Aug 2021 · 2 mos

• Worked across BI Data Science team and Threat Intel team to improve current classification model. Incorporated new data sources, externally through web scraping and internally using Clickhouse querying. Improved current model f1 score ~.10 through feature selection and feature engineering.

Jun 2020 – Sep 2020 · 3 mos · Palo Alto, California, United States

• Created backend framework incorporating stock forecasting for consumer live and back testing algorithmic day trading. Developed back-end framework in Google Cloud Platform using BigQuery, Pub/Sub, Cloud Scheduler, and serverless environment with CI/CD practice followed. Small startup team of five people placed top 5% at Walmart’s Forecasting Kaggle competition.

Sep 2019 – Jun 2020 · 9 mos · San Diego

• Data Science tutor for DSC10 (Principles of Data Science) and DSC80 (The Practice and Application of Data Science). Worked with professors and tutors of the courses to update/write homework questions, write test questions, grade, and answer questions on piazza (class online forum). Held office hours 3x a week to help students understand concepts/help on assignments. DSC10 covered introduction to python/pandas with basic statistics (CLM, A/B testing, confidence intervals). DSC80 was more application heavy, from hypothesis/permutation testing to using sklearn for imputation, NLP, web scraping, building data pipelines and cleaning data.

Jun 2019 – Sep 2019 · 3 mos

• Built a classifier using patients’ electrocorticograms (ECoGs) collected from the company’s RNS (Responsive Neurostimulator) medical device. Researched methods to work with noisy seizure data and implemented backend predictor to help guide physicians.

Nov 2018 – Jun 2019 · 7 mos

• Data science intern at SEO (search engine optimization) company. Developing a large-scale model that streamlines the process of analyzing website data utilizing NLP (normalization, feature extraction, tuning). Python, Pandas, and Sklearn used in Jupyter Notebook. Working independently under the CTO's supervision, tracking weekly progress using GitHub.

Jun 2018 – Sep 2018 · 3 mos

• Medicinal organic chemistry lab synthesizing novel compounds and analyzing data. Worked on confidential project, presented results of experiments at weekly meetings, and discussed future directions. Presented at Intern Symposium work done during internship. Learned basic organic chemistry lab techniques, how to utilize analytical machines, and developed a deeper understanding of the drug discovery and development timeline.

Nov 2017 – Apr 2019 · 1 yr 5 mos · UCSD Medical School

• Lab run by Dr. Wu at UCSD that studies axonopathy and its connection to neurodegenerative disease in humans. Analyzing data gathered from experiments using programs such as ImageJ to quantify trafficking direction and size as well as other properties of the cell. Learned biochemical techniques and work with live cell cultures.

Sep 2016 – Jun 2017 · 9 mos · UCSD

• Participated in a two course lab sequence researching the Streptomyces bacterium and the bacteriophage that infect it. Isolated a bacteriophage named Nikki and EM imaging was performed. The DNA Master program was used to analyze the genes and proteins certain bacteriophage produced, giving a greater understanding of the phage's anomalies. Learned different bioinformatics techniques and annotated the phage's genomes. Presented at the UCSD Undergraduate Research Symposium during the Spring of 2017.

Jun 2013 – Jul 2017 · 4 yrs 1 mo · Stanford University

• Worked at the Branner Earth Sciences library during summers. Catalogued maps in the Stanford Database using the Worldwide Library Database called Worldcat. Helped process and ship books as well as receive them and reentering them into the system.