Data Scientist

SQL,Python,Tableau,R,Hadoop Hive/Spark/Kafka,Rockset Database

Education

Bachelor of Engineering (Chemical Engineering) with Honours, National University of Singapore (Jun 2020)
Diploma in Chemical Engineering, Singapore Polytechnic (Mar 2014)

Data Scientist | Daikai Engineering Pte Ltd (Jun 2024 - Present)

Lead ETL processes using Python and MySQL, integrating data into Oracle Database.
Conducted in-depth Exploratory Data Analysis (EDA) on multi-variate time series, enhancing feature engineering.
Applied time-based clustering and graph-based semi-supervised learning to refine data annotation.
Developed LSTM Autoencoder models for anomaly detection across engines and vessels.
Authored and implemented company-wide PDPA policy.
Customized Kanban project management system using Kintone to enhance team coordination and efficiency
Provide comprehensive IT support, addressing hardware, software, network, server, and cybersecurity challenges to ensure smooth operations.
Initiated ad-hoc projects to aid sales efforts and improve workflow efficiency.

Process Engineer (Alarms) | Pfizer Asia Pte Ltd (Apr 2023 - Apr 2024)

Led a cross-functional team to revamp the GMP alarm management system.
Defined User Requirement Specifications for batch and periodic alarm reviews.
Implemented Statistical Process Control with control limits.
Spearheaded alarm reduction initiatives across multiple departments, achieving a 56% reduction in nuisance alarms in the initial phase.
Actively partook in continuous improvement projects.

Manufacturing Associate | Amgen Singapore Manufacturing (May 2021 - Dec 2022)

Specialized in single-use technology for biologic downstream purification.
Proficient in MES, LIMS, DeltaV, DCS, Control Studio, BOI, PI Vision, and Spotfire.
Ensured zero product loss during manufacturing operations.
Collaborated with subject matter experts on an OPEX project, reducing monthly operational costs by over $100,000.

Research Apprentice | Duke-NUS Medical School (May 2020 - Nov 2020)

Technical Executive Intern | TUV SUD PSB Pte Ltd (May 2019 - Aug 2019)

Administrative Executive | Singapore Armed Forces (Jan 2016 - Dec 2016)

Awarded with the Outstanding Servicemen Award in recognition of significant contribution to the unit.
Effectively planned for vehicular maintenance and manpower allocation according to dynamic demand.
Tactfully resolved administrative hurdles on a daily basis.

Anomaly Detection in Maritime Engines (Aug 2024 - Present)

Conducted Exploratory Data Analysis (EDA) on complex engine datasets to identify patterns and inform anomaly detection strategies.
Developing advanced anomaly detection models using techniques such as hierarchical clustering, label propagation, and LSTM-based autoencoders.
Pioneering innovative methodologies to improve predictive maintenance and operational efficiency.

EDA with SQL and Tableau for an Emergency Response Department (May 2024)

Utilized SQL to explore data and provided critical business insights for management team.
Built interactive and beautiful vizualizations using Tableau Public on EDA findings.

Hackathon - Hyperparameter Tuning in Neural Networks (Apr 2024)

Built a deep learning neural network to predict survival rate of passengers on the Titanic.
Utilized RandomSearchCV, GridSearchCV, Dask Tuner and Keras Tuner to optimize hyperparameters of a deep learning model.
Achieved a model accuracy of 83% on unseen data.

Set up Hadoop Cloud Ecosystem (Dec 2023)

Configured a functional Hadoop Hive/Spark/Kafka architecture using AWS EC2 through a Linux terminal.

Hackathon - Predictive Models (Nov 2023)

Built a regression model in python using Random Forest and Deep Learning algorithms to predict the commuting experience of passengers on the Shinkansen.
Model achieved 80% accuracy on unseen data.
Ranked 13th in global cohort of 45 teams.

Recommendation System (Nov 2023)

Built a product recommendation system using collaborative filtering and SVD Matrix Factorization in python to recommend products to target audiences in an online retail platform.
Model achieved an accuracy of 88.4% Recall and 85.4% Precision.
Key business insights and high value recommendations were proposed based on the analytics done.

Regression Models for Online Learning Platforms (Oct 2023)

Built a prediction machine using Random Forest and Decision Tree algorithms to predict the conversion probability of leads for an online learning platform (leads are audiences that showed interest in the programs).
Models were able to achieve a precision score of 83%, allowing business to focus their resources on clients that has an 83% likelihood to convert.

Exploratory Data Analysis on Foodhub business review (Sep 2023)

Conducted in-depth EDA on Foodhub data using python.
Delivered revenue-boosting insights through beautiful vizualizations and compelling storytelling.

Weight Profile Prediction (Jan 2020)

Built a predictive model that can project how a person’s weight will vary through their life, according to their personality archetype.
Model was pioneered using mathematical formulas from chemical engineering and key principles from behavorial psychology in python language.

Chromatogram Data Extractor (Jul 2019)

Automated the data extraction and transcription process from chromatograms using Excel VBA, reducing process time from 30 to 5 minutes.

Data Science Certificates

Engineering Certificates