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蚂蚁金服(杭州)网络技术有限公司
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Assessing your cultural and operational fit
University of Pittsburgh
Master's degree, Industrial Engineering
January 1, 2013 – January 1, 2015
Nanjing University of Aeronautics and Astronautics
Bachelor of Science (BS), Industrial Engineering
January 1, 2009 – January 1, 2013
蚂蚁金服
算法专家
July 1, 2018 – Present
浙江 杭州
华为
Machine Learning Engineer
December 1, 2016 – July 1, 2018
Hangzhou-Shaoxing Metropolitan Area
WitSpring
Data Miner
March 1, 2015 – November 1, 2016
Hangzhou-Shaoxing Metropolitan Area
Kaggle-predict click-through rates on display ads
December 1, 2014 – Present
The goal of this challenge is to benchmark the most accurate ML algorithms for CTR estimation. Methodologies Involved: Logistic Regression, Hashing Trick
Data analysis - Children’s Community Pediatrics Project
September 1, 2014 – Present
Using Linear Regression in Python analyzed 388,000 Children’s Community Pediatrics real patients data to assess the impact of offering walk-in hours on attracting urgent care patients and determined the best walk-in hours schedule.
Design a Database for an Automobile Company
April 1, 2014 – Present
*Created E-R diagram and relations for an automobile company and Built the database in Access *Worked with two teammates; in charge of building the database in Access *Methodologies Involved: E-R Model, Relational Model, SQL Queries
Data analysis - Homewood Children’s Village
February 1, 2014 – November 1, 2014
Analyzed 1,253 real students data, to evaluate the effectiveness of tutoring and mentoring programs at HCV; clustered the students into three performance groups and determined the threshold of HCV’s intervention time Methodologies Involved: K-means, Bayesian Analysis of change point, Backward Variable Selection Worked with two teammates; mainly contributed on R code created
Simulation about Air Traffic Control (ATC) Problem
December 1, 2013 – Present
Built a simple ATC model and simulated it based on discrete event based method Determined the best strategy with Selection of the Best algorithm Worked with two teammates; team leader; mainly contributed on Java code created
The Time Series Research about Solar Flares
July 1, 2012 – Present
Used historical data from NOAA to predict the strength of solar flares in Summer 2012, in order to find out the probability of the end of the world in December Created a model, and forecasted the result Methodologies Involved: GLM, AR, MA, ARMA, ARIMA, (Partial) Autocorrelation Function
Practical Machine Learning
Coursera
June 24, 2026 – Present
Exploratory Data Analysis
Coursera
June 24, 2026 – Present
Getting and Cleaning Data
Coursera
June 24, 2026 – Present
R Programming
Coursera
June 24, 2026 – Present
The Data Scientist’s Toolbox
Coursera
June 24, 2026 – Present
Cultural Fit Analysis
The candidate has a strong academic background in Industrial Engineering and diverse professional experience across different companies (WitSpring, Huawei, Ant Financial) and project types (Kaggle, ATC simulation, real-world data analysis for non-profits). This diversity suggests adaptability and a broad interest in applying data science to various domains. The role as '算法专家' (Algorithm Expert) and 'Machine Learning Engineer' aligns well with a data-driven culture. However, the projects are primarily personal or academic, and the professional experience descriptions are somewhat high-level, making a deep assessment of cultural fit challenging without more detailed behavioral insights.
Soft Skills & Operational Fit
The candidate's project descriptions indicate a problem-solving mindset and a structured approach to data analysis. Experience in team leadership and agile development suggests good collaboration and operational fit. However, without specific soft skill assessments, this remains an inference.