Chen Jin Email & Phone Number

San Francisco, California, US

• Collaborated closely with the Product Management and Machine Learning teams to proactively identify, assess, and propose valuable features for optimizing feed ranking models.
• Overhauled the attribution dashboard using Tableau to align with a novel subscription tracking system, significantly improving its effectiveness in supporting upsell strategies.
• Provided valuable support to cross-functional teams by conducting experiment sizing and in-depth analysis, generating statistically significant insights to inform data-driven marketing campaigns.

• Spearheaded the creation, rigorous testing, and refinement of sophisticated, highly automated quantitative trading strategies tailored for futures and cryptocurrencies
• Leveraged WebSocket communication protocols to efficiently fetch real-time market data from exchanges. Skillfully decoded and restructured this data to facilitate comprehensive analysis
• Employed Support Vector Machine (SVM) models for signal generation, further enhancing its efficacy through the integration of compressed sensing techniques
• Methodically evaluated an array of trading strategies, encompassing moving average crossovers, interdelivery spread, and cash-and-carry arbitrage techniques, to identify and capitalize on profit opportunities
• Skillfully harnessed asynchronous programming methodologies to interact with various APIs, seamlessly achieving event-driven functionality through the integration of Kafka, enhancing overall trading system responsiveness

Los Angeles, California, US

• Developed PyTorch-based Machine Learning models for predicting concrete strength (SAI) by leveraging laboratory fly ash data
• Conducted a comprehensive performance analysis, contrasting the effectiveness of Artificial Neural Network (ANN) against Gaussian Process Regression (GPR)
• Employed advanced data processing techniques such as DBSCAN clustering, SMOTE oversampling, and PyOD outlier detection to address modeling challenges
• Elevated model interpretability through the creation of insightful visualizations, including Shapley values and feature effect plots
• Collaboratively authored a research paper presented at the PACRIM Conference, hosted by the American Ceramic Society (ACerS)

• Delivered comprehensive data analysis services and presented project proposals to China's National Center for Cardiovascular Diseases
• Utilized Keras to build Convolutional Neural Network (CNN) capable of identifying abnormalities in 12-lead electrocardiograms
• Achieved an 88% accuracy in classification by fine-tuning hyperparameters and implementing moving averages on the signal data
• Streamlined and accelerated data retrieval processes and indicator calculations through the strategic implementation of multiprocessing in scripts

Los Angeles, California, US

Hangzhou, Zhejiang, CN

• Conducted extensive research on government financial data (2013-2018) pertaining to public budgets, government debt, and expenditures related to public safety and transportation, encompassing 334 cities and 2851.
• Curated and transformed raw data into 12 custom-defined score indices, employing data cleansing techniques to address missing values and enhance overall data quality
• Utilized advanced analytical methods, including clustering analysis and time series analysis, to assess regional risk levels and inform strategic financial leasing decisions

Master Of Science - Ms, Data Science

Bachelor Of Science - Bs, Statistics, Business Economics

The Global Economy Honors