
Algorithm Engineer at TikTok.
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
University of Michigan - School of Information
Master's degree, Information Analysis & Retrieval, Data Science
January 1, 2016 – January 1, 2018
University of California, Berkeley
History&film
January 1, 2014 – January 1, 2015
Huazhong University of Science and Technology
Bachelor, Communication and Information
January 1, 2012 – January 1, 2016
TikTok
Algorithm Engineer E-commerce
January 1, 2024 – Present
Singapore · On-site
Kwai Inc.
Algorithm Engineer
August 1, 2019 – January 1, 2024
Beijing, China
JD.COM
Algorithm Engineer
July 1, 2018 – July 1, 2019
Beijing, China
Quicken Loans
Data Scientist(intern)
January 1, 2018 – April 1, 2018
Detorit
Archipelagos, Institute of Marine Conservation
Data Scientist(intern)
May 1, 2017 – August 1, 2017
Samos, Greece
Tencent
Data Scientist(intern)
March 1, 2015 – August 1, 2015
Beijing,China
Scientific Skincare Search Engine
September 1, 2017 – Present
• A search engine that enables users to search skincare products based on their concerns and desired functionality. • Collected around 40,000 product details with ingredients information from Amazon API. • Used online authoritative ingredient dictionary as reference/supervised data when we assign functionality to groups of ingredients. Automatically add those functionality information as index into our documents . • Used TF-IDF to index all the documents and evaluate our model using MAP method.
Topological Network Analysis and Comparison of Mastodon Instances
September 1, 2017 – Present
The goal of this project is to describe the top five most populous Mastodon instances through the lens of network analysis. Our secondary goal is to describe how instances are connected to each other (for example, mastodon.social is connected to over 3,000 other instances of Mastodon). The decentralization of Mastodon may create a more ‘fractured’ experience, but perhaps one that is also more human: humans evolved to work in small communities and continue to work in small groups based on potential constraints of the human brain and time. These small, ‘local’ communities may allow users to express compassion to a greater extent, which has led to journalists referring to Mastodon as ‘Twitter without Nazis’. Given time and interest, we may explore if online harassment is indeed expressed less often than within the global Twitter universe.
User Behavior & Intensions behind Twitter Movie Twittering Using Spark and Hadoop
September 1, 2017 – October 1, 2017
The goal of this project is to analyze how twitters ratings different from IMDB’s ratings among different scales, and most importantly, trying to understand users intentions behind MovieTweeting behaviors. By doing that, we can give film companies intuitions of what type of genres are more likely to become popular in social media, why and when is the best time to do movie propagation,and etc.
Deep Learning
DeepLearning.AI
June 24, 2026 – Present
Algorithms
Stanford University
June 24, 2026 – Present
Mathematics for Machine Learning: Multivariate Calculus
Imperial College London
June 24, 2026 – Present
Cultural Fit Analysis
The candidate has worked in diverse environments, from large tech companies like TikTok and JD.COM to research institutes. Project diversity, including user behavior analysis, search engine development, and network analysis, suggests a broad interest and ability to adapt to different problem domains. The target role of 'Data Analyst' aligns well with the candidate's strong analytical and data processing background, although their experience leans more towards 'Algorithm Engineer' and 'Data Scientist' which often involve more advanced modeling and engineering tasks than a typical Data Analyst role. This could indicate a potential for overqualification or a desire to shift focus.
Soft Skills & Operational Fit
The candidate's project descriptions indicate an ability to identify user intentions, gather business requirements, and translate them into analytical solutions. Experience across different companies suggests adaptability. However, without specific psychometric test results or interview data, a detailed assessment of soft skills and operational fit is limited.