Jing Y.

2010 to 2014

@Hangzhou
2014 to 2015

@New York City
2019 & 2020

@Vancouver, Canada
2016 to present

@Bay Area of San Francisco

Hello world, my name is Jing. I am

a Machine Learning Practitioner solving real world problems
with 5 years industry experience
confident in self-driven capability to build things from scratch.

Focusing on Natural Language Understanding, Auto Machine Learning, Model Explanation, Feature Engineering.

Please feel free to reach me at joyceye04@gmail.com or any media below

Work

Applied Data Scientist

SAP Labs

Productize machine learning in SAP CRM Cloud for Sales & Service to accelerate business processing.

Design and implement machine learning driven solutions with full lifecycle development from model design, feature engineering, model training to model server deployment and inference.

Deliver statistical analysis, model performance evaluation and data visualization to support PM and Customer Success teams.

User cases: Note Intelligence, Opportunity Scoring, Lead Scoring, Sales Product Recommendation, Knowledge based Question Answering, Ticket Tagging, Auto Compose, Auto Feature and more.

Highlight: AutoML, Feature Engineering, Natural Language Understanding

Oct 2016 - Present

Machine Learning Engineer

Intellipro

Designed and built machine learning models (k-means, lasso regression, genetic algorithms) for automated management of containerized application system performance as enterprise cloud service (aka Auto DevOps).

Implemented demo features such as real-time key factor detection, anomaly detection, diagnostic root analysis, capacity planning with optimized configuration.

Skills: Spark, Kafka, Docker, Rancher, Influx DB and etc.

Feb 2016 - Oct 2016

Data Scientist

Dropthought

text classification and sentiment analysis for customer reviews.

May 2015 - Oct 2015

Product Analyst

NetEase Inc.

Improved product functionality and user experience by analyzing web traffic data using SQL and Google Analytics.

Nov 2013 - Apr 2014

Projects

SLiM

A Stock Analysis Tool with

Charting: moving average (sma, ewma) chart, candle chart;

Scraping: daily prices, financial stats, blogs, RSS, gurus trade history, insiders buy and sell, peer comeptitors, suppliers;

Strategies: not public

Machine Learning Playground

Implement machine learning models from scratch.

Decision Trees, Knn, KMeans, CNN, RNN and etc.

A Data-Driven Approach for Energy Management

@Sustainable Engineering Lab at Columbia University

Forecasted energy demand of 30 cities in 3 years by grouping peer-cities with k-means clustering and predicted seasonal trends with Holt-Winters time series model, visualized graphical and numerical results with ggplot2 and d3.js.

Vengo Optimization

@Vengo Inc. & Columbia University

Cooperated with a New York based startup Vengo Inc. to increase sales revenue by optimizing product combinations in different interactive vending machines according to customer segmentation based on location separation using non-linear programming and time series models.

Education

Columbia University

Master of Science, Operations Research

Sep 2014 - Dec 2015

Zhejiang University

Bachelor of Science, Mathematics

Sep 2010 - June 2014

Skills

Programming: Python, JAVA, SQL, C++, HTML, CSS, JavaScript

Tools: Docker, Spark, Kafka

ML dependencies: XGBoost, CatBoost, Hyperopt, TensorFlow, Keras, spaCy, NLTK, Sklearn