As an experienced Software Engineer, construct products to achieve various goals such as data collection/pipelines, features under intensive requests and other typical cloud applications.
Beyond building features and products, as a Site-Reliability Engineer, to locate, and improve system problems in a fast-pacing and great-stress environment. On top of that, being capable of creating tools to reduce the costs in maintenance operations based on failed operations/outages.
Last but not least, as a machine learning engineer/ financial researcher, from data analysing and cleaning to landing those models as tools or products to meet various internal and external requirements. Also, submitting patents to protect the company’s domain know-how.
Quantitative Developer, Software Engineer, Full-Stack Developer
Taipei,Taiwan
[email protected]
Languages: C++ (MBA dissertation), Python3 (prior work experience in computing server and MSc dissertation), Javascript (prior work experience), Go (prior experience in quant finance), R (prior work experience in statistic system), Java (MSc course projects), Haskell (constructing lambda calculus), Kotlin (Personal Project in Android)
Technologies: Tensorflow2 (MSc dissertation), Pandas (prior work experience and Coursera certification), Numpy (prior work experience), Ubuntu Server/ CentOS Server/ AngularJS/ MariaDB/ MongoDB/Docker/ Flask/ Nginx/ Apache2/ Yii2 (prior work experience), React.JS/ Vue.JS/ Android Studio (Personal Projects)
Specialities: Agile methodologies (software engineering project), Deep Neural Networks/ Reinforcement Learning/ Meta-learning (MSc Dissertation)
◆ Constructing an application server as the system kernel to coordinate various teams to deal with system crash accordingly based on statistical and machine learning models, which led to reducing 50% of the outages’ recovery time during the peak time.
◆ Build up command line tools and CI/CD flow to improve the MLOps flow in both the most time-consuming phases - deploying and training
◆ Adopting Pulumi to enhance the original IaC development flow and collecting system data through both hosted service and self-made worker – GCP Composer and Kubernetes Cronjobs
◆ Building up a brand new Slackbot system to support SRE daily tasks, routine operations, and on-call activities, which not only help SREs to develop tools easily but also upgrade the legacy system into the cutting-edge tech stacks
◆ Efficient developing pace but always with unit tests to cover/ guard the expected outcomes of those features – above 80% coverage rates
◆ Refactor refund mechanism, which results in improving around 71.64% latency under SQL row lock constraint
◆ Through re-designing, refactoring, and implementing around 20 high loading endpoints to utilise CDN cache, which not only has the system sustain 50X amounts of the last highest requests but also be compatible with prior- and pot- versions
◆ Integrating the third-party payment method – DotMoney – with the company’s payment system
◆ Constructed a crowdfunding platform, offering users to showcase their works to the potential founders and their friends, through vivid functionalities, stable APIs and automated testing and CI/CD backend system
◆ Constructed an asynchronous trading system, which led to utilising novel machine learning models to do high-frequency trading (HFT) in the largest cryptocurrency market, implementing low-latency trading logic, and offering well-designed logging and alert mechanism.
◆ Conducted trading model documents, offering some insights in both the design of the
reinforcement learning models and the mechanism of the financial market.
◆ Devised statistic methods and novel quantitative models by Go, Python and R, offering unique trading indicators to our customers and compiling the advantages of our partners
◆ Conducted academic research and daily market report, convincing more Securities and Futures companies to join our platform and enhancing the platform with more potential features
◆ Managed and secured customer data by MariaDB and Unix-like operating systems, which led to discovering the potential demand from using behaviours of our users and protecting user data
◆ Crawled over 50 different data sources from the worldwide by operating customised crawling robots, offering the newest financial data and presenting distinct mathematical indicators to investors
◆ Constructed various quantitative models including the Black-Scholes-Merton model, binomial tree and derivatives models by C++, providing over 30 different pricing models to the company
◆ Solved connecting problems among different computing languages and database languages, which led to utilising C++ library in Python and building the connecting interface of C++ to MongoDB
This programme involves studying modern artificial intelligence models. Units include reinforcement learning, intelligent control and cognitive systems, functional programming, database, cryptography. In this programme, I have built Deep Q-Network and tabular methods to solve traffic light control problems, have learned to create a game through Java under an agile framework and have created an interactive wall-following robot. In addition, I have built a CYK parser and turtle compiler through C, and Lambda-Calculus through Haskell.
This degree mainly focuses on financial engineering, including Stochastic calculus, Interest rate derivatives, Advanced financial engineering. The dissertation was titled ‘Frequent Trading to the Impact of Options Liquidity’. The analytical programme is written, using C++ to examine the change of microstructure in the Options market.
As an experienced Software Engineer, construct products to achieve various goals such as data collection/pipelines, features under intensive requests and other typical cloud applications.
Beyond building features and products, as a Site-Reliability Engineer, to locate, and improve system problems in a fast-pacing and great-stress environment. On top of that, being capable of creating tools to reduce the costs in maintenance operations based on failed operations/outages.
Last but not least, as a machine learning engineer/ financial researcher, from data analysing and cleaning to landing those models as tools or products to meet various internal and external requirements. Also, submitting patents to protect the company’s domain know-how.
Quantitative Developer, Software Engineer, Full-Stack Developer
Taipei,Taiwan
[email protected]
Languages: C++ (MBA dissertation), Python3 (prior work experience in computing server and MSc dissertation), Javascript (prior work experience), Go (prior experience in quant finance), R (prior work experience in statistic system), Java (MSc course projects), Haskell (constructing lambda calculus), Kotlin (Personal Project in Android)
Technologies: Tensorflow2 (MSc dissertation), Pandas (prior work experience and Coursera certification), Numpy (prior work experience), Ubuntu Server/ CentOS Server/ AngularJS/ MariaDB/ MongoDB/Docker/ Flask/ Nginx/ Apache2/ Yii2 (prior work experience), React.JS/ Vue.JS/ Android Studio (Personal Projects)
Specialities: Agile methodologies (software engineering project), Deep Neural Networks/ Reinforcement Learning/ Meta-learning (MSc Dissertation)
◆ Constructing an application server as the system kernel to coordinate various teams to deal with system crash accordingly based on statistical and machine learning models, which led to reducing 50% of the outages’ recovery time during the peak time.
◆ Build up command line tools and CI/CD flow to improve the MLOps flow in both the most time-consuming phases - deploying and training
◆ Adopting Pulumi to enhance the original IaC development flow and collecting system data through both hosted service and self-made worker – GCP Composer and Kubernetes Cronjobs
◆ Building up a brand new Slackbot system to support SRE daily tasks, routine operations, and on-call activities, which not only help SREs to develop tools easily but also upgrade the legacy system into the cutting-edge tech stacks
◆ Efficient developing pace but always with unit tests to cover/ guard the expected outcomes of those features – above 80% coverage rates
◆ Refactor refund mechanism, which results in improving around 71.64% latency under SQL row lock constraint
◆ Through re-designing, refactoring, and implementing around 20 high loading endpoints to utilise CDN cache, which not only has the system sustain 50X amounts of the last highest requests but also be compatible with prior- and pot- versions
◆ Integrating the third-party payment method – DotMoney – with the company’s payment system
◆ Constructed a crowdfunding platform, offering users to showcase their works to the potential founders and their friends, through vivid functionalities, stable APIs and automated testing and CI/CD backend system
◆ Constructed an asynchronous trading system, which led to utilising novel machine learning models to do high-frequency trading (HFT) in the largest cryptocurrency market, implementing low-latency trading logic, and offering well-designed logging and alert mechanism.
◆ Conducted trading model documents, offering some insights in both the design of the
reinforcement learning models and the mechanism of the financial market.
◆ Devised statistic methods and novel quantitative models by Go, Python and R, offering unique trading indicators to our customers and compiling the advantages of our partners
◆ Conducted academic research and daily market report, convincing more Securities and Futures companies to join our platform and enhancing the platform with more potential features
◆ Managed and secured customer data by MariaDB and Unix-like operating systems, which led to discovering the potential demand from using behaviours of our users and protecting user data
◆ Crawled over 50 different data sources from the worldwide by operating customised crawling robots, offering the newest financial data and presenting distinct mathematical indicators to investors
◆ Constructed various quantitative models including the Black-Scholes-Merton model, binomial tree and derivatives models by C++, providing over 30 different pricing models to the company
◆ Solved connecting problems among different computing languages and database languages, which led to utilising C++ library in Python and building the connecting interface of C++ to MongoDB
This programme involves studying modern artificial intelligence models. Units include reinforcement learning, intelligent control and cognitive systems, functional programming, database, cryptography. In this programme, I have built Deep Q-Network and tabular methods to solve traffic light control problems, have learned to create a game through Java under an agile framework and have created an interactive wall-following robot. In addition, I have built a CYK parser and turtle compiler through C, and Lambda-Calculus through Haskell.
This degree mainly focuses on financial engineering, including Stochastic calculus, Interest rate derivatives, Advanced financial engineering. The dissertation was titled ‘Frequent Trading to the Impact of Options Liquidity’. The analytical programme is written, using C++ to examine the change of microstructure in the Options market.