Chee Yee Lim
Data Science Team Lead
Portfolio
A selection of dashboards built using Python Dash and public data, with a sprinkle of machine learning.
Optimisation Visualiser
Dashboard to visualise algorithms searching on optimisation surface.
Open Dashboard
Singapore Resale HDB Analytics
Dashboard to understand the pricing history of HDB resale flats.
Open Dashboard
Experience
Data Science Manager
July 2023 - PresentJohnson & Johnson, Singapore
- Manages a team of data scientists in Global Finance to deliver on various forecasting projects.
Data Science Manager
June 2022 - June 2023Senior Data Scientist
Sept 2020 - June 2022DHL Consulting, Singapore
- Managed a team of 3 data scientists both as a team lead and a project manager with a focus on empowering them to deliver business values using data science.
- Completed 8 data science projects (5 of which are in production) that solve business problems for clients, ranging from fraud detection to customer retention.
- Delivered an estimated total annual savings of SGD 860,000 while achieving an average customer satisfaction Net Promoter Score of 68.8 via the projects.
- Partnered closely with business stakeholders to jointly define problem statements and align priorities, so that projects can be delivered on time and within budget while satisfying clients’ needs.
- Led business development meetings and workshops with cross-divisional regional or country heads that brought in 5 data science projects, totalling SGD 570,000 in revenue.
- Communicated complex technical topics to business audiences using analogies to obtain buy-ins, which result in stronger confidence and engagement with our data capability.
- An example project delivered is a customer service analytics data product that highlights trending topics and associated KPIs (e.g. sentiments) from incoming customer chats, emails and calls using Natural Language Processing (NLP), resulting in shorter response time, lower staffing cost and improved service quality for our client.
Data Scientist
July 2019 - Sept 2020PatSnap, Singapore
- Developed a random forest-based model for patent value prediction by integrating novel NLP-based metrics extracted from patent texts with traditional patent indicators.
- Deployed the random forest-based model into production in 2 forms: (1) as a dockerised Flask API for generating real-time predictions on new data, and (2) as a PySpark pipeline for generating batch predictions on historical data.
- Worked closely with a team of 3 product managers and 2 engineers to ensure the product is developed on time while achieving business goals and fitting into existing IT infrastructure.
- The patent value product replaced a third-party patent value data provider, which helps our company saves $100,000 per year in subscription fee.
Data Scientist
July 2019 - Sept 2020Schroders, UK
- Led the development of the human capital data product to provide summary insights into the board director relationships and career histories for 20,000+ public companies globally.
- Engineered the backend ETL using distributed processing in Spark and the frontend using R Shiny dashboard.
- The final product was perceived as 'a distinct value-add and massive time saver' by the heads of 3 investment research teams who requested their analysts to use the product as part of their process.
- Liaised with 9 data vendors and verified the quality of alternative data by checking their data collection and processing methodology, as well as comparing the data with known information.
PhD Researcher
October 2013 - September 2017University of Cambridge, UK
- Used machine learning techniques to study how stem cells make developmental decisions by analysing terabytes of time-series single-cell expression data.
- Reconstructed the development timeline with a polynomial model fitted to a kernel PCA-reduced space, which enables the subsequent inference of potential causal relationships among genes using penalised vector autoregression and Boolean models.
- The research resulted in 2 research papers, one of which is a first-authored paper.
- Commended by at least 3 senior researchers on my public speaking ability in presenting complex technical terms clearly and passionately.
Education
University of Cambridge, UK
October 2013 - September 2017PhD in Computational Biology
- Graduated on-time with 2 research papers and presented a poster at the ISMB conference.
- Tutored for 2 bioinformatics courses and led the Wolfson College Table Tennis team.
University of Edinburgh, UK
September 2010 - June 2013BSc (Hons) in Genetics
- Achieved 1st class despite skipping the first year of study via direct entry to the second year.
- Represented 30 students as a class representative and voiced out concerns affecting students.
Skills
Programming Languages & Tools
Machine Learning & Statistical Methods
- Exploratory Data Analysis
- Natural Language Processing
- Time-series Data Analysis
- Traditional Machine Learning
- Statistical Analysis
Human Languages
- English - Fluent
- Mandarin - Native
- Malay - Intermediate
- Cantonese - Conversational
Achievements
Certifications
- Google Cloud Trainings ( View)
- Passed CFA level 1
- Investment Management Certificate
Publications
- Distinct molecular trajectories converge to induce naive pluripotency. Cell Stem Cell September 2019. ( View)
- Understanding transcriptional regulation through computational analysis of single-cell transcriptomics. Doctoral thesis September 2017. ( View)
- BTR: training asynchronous Boolean models using single-cell expression data. BMC Bioinformatics September 2016. ( View)
Interests
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Table tennis
Enjoy the intense focus required and rapid adaptability nature of table tennis in competitions.
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Meetup events
Attend Meetup events regularly to keep up with the latest development, and to network with people from different backgrounds.
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Travel
Enjoy hiking in nature and experiencing different culture in a foreign country.