Sarah Wang is a quantitative researcher, data scientist, and software engineer. She is a success-driven, intellectually curious, and highly collaborative individual with 5 +years of experience in global capital markets and expertise in data-intensive analysis. She is also the winner for Miss Asia Canada.
As a quantitative researcher, She has worked on the full lifecycle of systematic investment, from factor back-testing and model implementation, to portfolio construction and risk management. She has hands-on experience across all asset classes, including Equity, Fixed Incomes, FX, Commodities, Credit, and Derivatives.She believes that extensive research and cutting-edge technology are the keys to generate superior risk-adjusted return throughout market cycles.
As a data scientist, she enjoys drawing insights from data and helping guide business decisions. She is proficient in predictive models, data processing, and machine learning algorithms.She is capable of creating, developing, and testing highly scalable and complex architectures to translate business questions to substantial deliverables.
As a software engineer, she co-founded a Toronto-based technology start-up focusing on revolutionizing post-COVID dining experience, and served as solution-oriented CTO managing a team of 20 professionals focusing on product management and software development. She designed complex full stack architecture with React-Native, MongoDB, and GCP, and designed the DevOps process for a smooth release process to provide timely solutions for clients. She provides effective leadership in fast-paced, deadline driven environments, and works across business and technical teams to increase profits and reduce costs through continuous improvements and strategic technology infrastructure planning.
Aspect-based Sentiment Analysis in Document - FOMC Meeting Minutes on Economic Projection (Tensorflow, Keras)
Predict realized volatility in equity market from intra-day data (pytorch)
Applied multiple machine learning algorithms (k-NN and decision trees) in Matlab and Python to analyze Uber’s current consumer base and made recommendations on future marketing strategies
Predict whether a given airline will suffer from major flight delay due to weather conditions
The effects of mandating face masks in public facing businesses in United States
Predict housing prices based on demographic information
A baseline research and implementation on mean variance portfolio optimization with transaction costs. Idea comes from literature Quantitative Equity Portfolio Management by Ludwig B. Chicarini and Daehwan Kim
Develop an integrated mobile and website system that acts as a touchless system for customers and creates a seamless dine-in and takeout experience in the Greater Toronto Area
Python, PySpark, R, C++, Shell, Javascript, etc.
Scikit-Learn, Tensorflow, Keras, etc.
SQL, NoSQL, KDB+, etc.
Jenkins, Docker, etc.
GCP, and AWS.
Master of Information & Data Science
Machine Learning, Data Engineering, Statistics, Natural Language Processing, Big Data, Experimental Design, Research Design, Data Visualization, etc.
Bachelor of Computer Science & Finance
Algorithm, Statistics, Advanced Mathematics, Database Design, System Design, Financial Asset Pricings, Portfolio Management, etc.
CFA charterholder, Part-time CFA instructor
The DNA of Top Performers
Self-awareness, leveraging feedback, goal-setting, career strategy, handling adversity and managing your reputation are only a handful of the topics covered.
Amazon Web Services Cloud Practitioner
Neural Networks and Deep Learning, Machine Learning by Stanford University