Resume
Experience
June 2022 - August 2022
Data Engineer Intern
McKinsey & Company
New York City
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Drove the tech workstream for a big pharmaceutical client which involved architecting a centralized data operational repository to allow for data-driven marketing decision
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Conducted prioritization evaluation of 12 different systems to create a three wave development approach based on business value and tech feasibility which reduced time needed to achieve 80% of total usable data capacity by 6 months
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Developed a holistic tech roadmap with the key considerations and deliverables required to produce the end-to-end solution
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Detailed key technical requirements for an AI solution; created an actionable optimized deployment plan accounting for key constraints and deadlines to increase percentage of timeline requirements met from 35% to 100%
September 2022 - Present
Data Science Consultant
UCLA Library
Data Science Center
Los Angeles
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Consult to curate, transform, visualize and analyze researcher data using Python, R & Tableau
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Member of UCLA Data Squad, a student run team within the UCLA Library Data Science Center
June 2021 - September 2021
Data Science Intern
Zectr
Hong Kong / United States
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Developed a Scrapy API and NLP engine to obtain and analyze the Amazon reviews for any product
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Operationalized the engine using a Python Flask backend integrated with JS frontend to enable clients to easily generate market research reports on large amounts of data in real-time.
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Reduced the hours required to manually analyze free-form response surveys from 3-4 hours to less than 20 minutes by developing and deploying a multilingual free-form response engine that automatically structures and analyzes the keywords, phrases, topics within a survey using various data science algorithms such as LDA (Latent Dirichlet allocation) and PCA (Principal Component Analysis); Worked with a BERT English models and an Ernie Chinese models to classify the response and keyword sentiments.
October 2020 - Present
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Head People Analyst
DataRes
Los Angeles
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Developed a team matching algorithm using cosine similarity to automate the process of matching the professional interests and skills of 30 members in our summer prep course. This team matching algorithm ensured each of the six teams were capable of delivering strong projects, and individual members get opportunities to explore unknown sub-spheres within Data Science by practicing new tools/methods outside of their current knowledge.
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Analyzed past recruitment data to increase diversity and quality of future applicants by targeting certain applicant sources. Devised 3 key recommendations that will be implemented during the Fall 2021 recruitment cycle.
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Created and led several data science workshops for 40 other members including an introduction to machine learning course and a mock interview course for statistical concepts such as A/B Testing and Algorithmic Design.
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Collected quarterly survey data from teams and members to provide insights to the rest of the board about what DataRes members should be doing better to break into different roles in data science.
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Optimized the gamma, beta and n_steps within a Deep Reinforcement Learning Model that uses Policy Gradients to teach an Agent to trade stocks; learned from the agent to take a passive long-term approach when trading.
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Analyzed over 16,000 free-response customer survey responses for Basepaws by applying unsupervised machine learning to learn which factors correlate the most with cat diseases.
October 2020 - Present
Vice President
Bruin Sports Analytics
Los Angeles
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In charge of developing the technical data science skills of new/existing members in order to empower anyone interested in the field of sports analytics to be equipped with the skills to write adequate data journalism articles.
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Furthermore, in charge of ensuring intermediately skilled existing members can develop their data science knowledge further to be better suited in landing a job within the sports analytics industry
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Explored, analyzed and published articles about various statistical applications to the sports field including the importance of the serve in Tennis, and data-driven tips to crack the fantasy soccer process.
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Performed stochastic mathematical modelling to simulate and predict the results of the latest Indian Premier League. Compared and contrasted this model to a traditional K-Nearest-Neighbours model to extract valuable insights about the current season's Indian Premier League
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Created visualizations and dashboards for the social media page of the club to illustrate key insights within the sports field.
October 2020 - Present
Data Science Consultant
Data Science Union
Los Angeles
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Created an Age-Guesser using Transfer Learning on a VGG19 model using over 50,000 images of celebrities scrapped from wikipedia and IMBD; the final model predicted 75% of images within 5 years of their actual age.
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Worked on several client projects including the food-delivery start up Duffl to develop a product recommendation system that uses both collaborative and content-based filtering to ensure new/existing products are adequately recommended to users.
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Used NLP libraries in Python such as gensim and NLTK to group foods with similar ingredients and food descriptions together.
January 2021 - May 2021
Project Lead
Fedo.ai​
Los Angeles/Bangalore
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Lead a team of four students to develop a convolutional neural network image classifier that was able to predict whether or not a person was a smoker with a 71% accuracy.
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Improved the baseline model performance from 55% by using various image-preprocessing techniques such as Hessian filters, Laplace transformations and auto-cropping to reduce background noise.
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Ensured biweekly deliverables were given to our client to update them on our progress, and future direction.
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Apart from this image classifier, I also analysed over 100,000 health records from 2013 to 2017 to develop a Random Forest classifier model to predict whether or not someone has diabetes based upon 5 key features with a 86% accuracy.
July 2020 - September 2020
Data Science Research Intern
Hong Kong
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Created an application to track tasks of users in the company and award XP points for the completion of tasks based on priority, effort and due date using Asana’s open API.
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Analyzed data from the application using Python's Numpy and Pandas libraries to devise a new methodology called Internal Analytics; this improved worker task completion by 61%.
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Analyzed Google Ads and Analytics data using BigQuery and Mixpanel to compile reports for clients with data-driven recommendations for future marketing campaigns; improved the effectiveness of campaigns by 41%.
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Published blog posts on why BigQuery’s Machine Learning is a must-use by today’s marketers and presented these findings to 96 other employees in the company.
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Assisted in developing a process called Proactive Analytics, which takes a scientific approach to digital strategy.
July 2017 - July 2019
Corporal
Singapore Armed Forces
Singapore
Using the large database E-HR, organized the medical documentation and welfare of the soldiers from the commando formation.
As a green beret Corporal, led the deterrence and defence of Island Defence security threats, and accounted for the rifles and ammunition of 250 other soldiers
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Education
August 2019 - Present
University of California, Los Angeles
B.S. in Data Theory
Major GPA: 4.0
Cumulative GPA: 3.99
Los Angeles
Activities and Societies: Project Lead at Data Science Union, Head People Analyst at DataRes, Head of Membership Development at Bruin Sports Analytics, Fitness and Nutrition Instructor and Intern for SCOPE, Toastmasters Member
Honors: Deans Honors List (All Quarters)
Relevant Coursework: Calculus of Several Variables, Programming with C++, Computational Statistics with R, Linear Algebra. Experimental Design, Data-Driven Mathematical Modeling, Regression Analysis
August 2010 -June 2017
King George V School
International Baccalaureate (42/45 points)
Hong Kong
Activities and Societies: Student Prefect, Student Council Sub-Committee for Teaching and Learning, Event House Captain for Cricket, Academic Tutor, 24 Hour Race
Honors: ESF Chairman's Award For Excellence
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Higher Level Subjects: Mathematics, Economics, Psychology
Skillset
Data Analysis
Microsoft Excel, Word and Powerpoint
Google Analytics and BigQuery
Python; Libraries: Numpy, Pandas, Matplotlib and Scikit-learn
English
Mandarin Chinese