Three words about me: open-minded, easy-going, self-motivated
- Chinese native
- English professional proficiency
- Swedish basic
Check my data scientist journey picture on the homepage, it covers there!
M.Sc. KTH, Royal Institute of Technology School of Electrical Engineering
Deep Learning Specialisation deeplearning.ai
Machine Learning with TensorFlow on Google Cloud Platform Google Cloud
B.Eng. Southeast University, School of Information Science and Engineering
Machine Learning Specialisation University of Washington
Growth Manager & Senior Data Analyst at Volvo Cars
(2021 – Now)
Working different roles for different online business areas, but data and insights is always the core.
Data Scientist at Epidemic Sound
(2019 – 2021)
Working as an embedded product analyst in a Growth team which focuses on increasing organic traffic and optimising online user experience in early stage, responsibilities include reporting, providing insights, designing experiments, analysing AB tests results and contributing data infrastructure.
Conversion Specialist at Conversionista
(2017 – 2018)
Different data science projects:
– Improve online user experience, e.g. Recommendation Engine, Personalisation Content
– Automate the marketing process on GCP.
– Conversion review for online e-commerce and provide AB testing hypothesis and rule of thumb suggestions
– Heuristic tests for online e-commerce with Google Partners
Data Analyst at H&M
(2017 – 2017)
– Seek business insights for different concepts e.g. H&M +, H&M Sports from data perspective
– Analysing the trend of fabric composition among popular apparel retailers
Price Analyst at eDreams ODIGEO
(2016 – 2017)
Working as price analyst in the revenue team, the main focus of the job is to optimise the pricing model of online products which can quickly adjust to the variable market with competitive prices and to achieve the optimal balance between revenue and sales through AB testing.
Master Thesis Researcher at Ericsson
(2016 – 2017)
This master thesis project is about applying machine learning algorithms on data from radio access networks to predict the future incoming traffic. The research was focused on feature engineering the patterns of the traffic for the prediction model.