A bit about me
I'm a data scientist. I was born in Shanghai, and now live and work in London since 2018. Except for coding, I love new techniques, traveling, and cooking! Welcome to my portfolio and enjoy diving!
Data Scientist.
I currently work as a senior data scientist on consumer program in Philip Morris International. Before that, I have four year working experiences as a data scientist in Natwest Group and CACI after graduating from University College London where I hold a master's degree in smart cities and urban analytics, mainly solving spatio-temporal urban challenges.
- Age: 28
- Website: yurunsang.github.io
- Phone: +44-7422920701
- Now live: London, United Kingdom
- Gender: Female
- Degree: Master
- Email: yurunsang@icloud.com
- I am from: Shanghai, China
Besides work, I love travelling, cooking and gaming! I also have a one-year-old Maltese girl with me and her name is Luna! Welcome to my portfolio and enjoy diving!
Skills
Expertise in data analysis, with a strong foundation in statistical methods and experience using tools such as Python and R. A self-starter with excellent problem-solving skills, able to find creative solutions to complex challenges. Skilled in project management, with a track record of delivering high-quality projects on time and within budget.
Resume
- Data Scientist (Python/R/SQL): Built machine learning models for the bank and largest property owners across the UK and Europe, including transaction data, CRM, mobile data, consumer segmentations and survey data.
- Business intelligence (Tableau/Qlik):Designed both data models and interface for client-facing dashboards which display key metrics to monitor the specific needs of clients interactively.
- ETL (SQL/Python/Alteryx): Built pipeline updating process for thousands of survey data and developed an in-house web tool to allow non-technical people to use. Designed process for generating batch automations and reports.
Summary
Runsang Yu
Innovative and passionate data scientist with 4+ years of experience designing, building, and deploying machine learning models to solve real world problems.
- 44 Felnex Avenue, London, United Kingdom
- +44-7422920701
- yurunsang@icloud.com
Education
Msc & Smart Cities and Urban Analytics
2017 - 2018
University College London, London, United Kingdom
Applied advanced techniques to conduct spatial-temporal big data challenges. Core modules: Quantitative methods; Geographical information systems; Spatial-Temporal Data Mining; Spatial capture and analysis; Urban simulation
BEng & Civil Engineering
2013 - 2017
University of Shanghai for Science and Technology, Shanghai, China
Core modules: Structural mechanics, Fundamental of structural steels, Structural Engineering
PERSONAL PROJECTS
Data Insight Scientist
2021 - 2022
COMMUN Ltd, London, United Kingdom
Professional Experience
Manager Segmentation and Modelling
2022 Dec - Present
Philip Morris International, London, United Kingdom
- Lead in customer segmentation, lifetime value, churn models across global markets to support customer lifetime journey.
Data Scientist
2021 Oct - 2022 Dec
RBS International, Natwest Group, London, United Kingdom
- New Branches Queueing Tool Simulation: Developed a queueing tool in a web interface using Python to simulate the branches traffic under different scenarios to help stakeholders make decisions on closing or remaining the branch.
- Business Through Personal Accounts Identification: Built a clustering model based on time series features to identify accounts that are making business transactions through personal accounts.
- Customer Mortgage Retention Analytics: Built a classification model for mortgage customer behaviours when rolling onto standard variable rate products, predicted customer's likelihood to churn in the next three months
Data Scientist
2018 Sep - 2021 Sep
CACI, London, United Kingdom
- GPS data: Developed people's favourite places using GPS location data and POI data to support leasing strategy and modelled out trip purposes to generate more insights for clients. Modelled out thousands of users’ home/work locations using DBscan based on millions of GPS location data.
- Consumer Segmentation Model: Used over ten thousand of questionnaire data to build a consumer segmentation model in the UK with a combination of unsupervised learning methods.
- ETL Process: Built the ETL process automation for one of the company’s biggest benchmark products for all the UK shopping malls.
- Social Distancing Model: Developed an Agent-based Model in NetLogo to simulate how clients can ensure their staff to return office safely under the social distance policy.
- Sales Daily Forecasting Model/Customer Repurchase Likelihood Model: Developed machine learning models on Azure Databricks to forecast the daily sales for one of the biggest e-commerce companies and to predict the repurchase likelihood of new customers to help clients on marketing decisioning and boost the retention rate.
