Rachel H.

Led the development of systems for trading, risk control, and client relation management; optimized investment workflow by systematizing data ingestion, portfolio management and generation, instruction generation, and risk management systems.

1. Algo Trading System

    

   I utilized Go, Java, and Python for the development of a low-latency Algo trading system, including numerous microservices that covered pricing engines, quick trade service, API gateway, order automation engine, and optimization of trading algorithms. The system outperformed 95% of the participants in the hedge fund market.
   Additionally, I built an operational risk control layer on both UI and engine levels to ensure a secure and reliable trading experience.

   Full-Stack Engineer, Node.js, Python, AWS, Java, Vue.js, Go, SQL, Django, Spring Boot, MySQL, CSS, Microservices, Spring Framework, CI/CD, HTML, MongoDB, Agile, Data Visualization, Scala, JIRA, Visual Basic, jQuery, Redis, GitLab, NumPy, RabbitMQ, Splunk

2. Client Service Reporting System

    

   I utilized Go, Java, Python, MySQL, and Django to independently develop the Client Service Reporting System, a website that included features such as data visualization of performance attribution, market and investment analytics, real-time feed of risk alerts and market news, all tailored to the preferences and positions of individual clients.
   It saw the AUM rise from USD 400 million to USD 2 billion.

   Full-Stack Engineer, Product Manager, JavaScript, Python, AWS, Java, Vue.js, Go, Django, MySQL, Microservices, Scala, GitLab, RabbitMQ

3. Portfolio Generation System

    

   I built a portfolio management system that carried out daily adjustment on our two-billion-dollar portfolio based on the dynamic optimization between three elements: 1) the liquidity of the invested products 2) allocated risks of the invested products 3) current cash holdings. The array of products covered in the PMS included over 1,000 stocks, over 500 bonds, over 100 commodities, and various other derivative instruments.
   It integrated PM/Research view with market data to generate trades and positions systematically, while maintaining effective risk control management.

   Backend Engineer, Python, AWS, Java, SQL, Scala, SFTP

Supported global (HK, LN, NY, TK) desks in the FICC department; independently designed and owned multiple features and services that solidified as standard practices

1. Distributed Market Data Calibration System

    

   I spearheaded the development of a distributed system that utilized WPF, C#, Scala, and Java, creating a platform that allows users to consume real-time market data and execute trading and other calculation-intensive tasks with extremely low latency.
   Additionally, I introduced the concept of data milestone for interest rate products in the market data domain, doubling the cache hit rate, and reducing heavy real-time calculation time by 2/3. This milestone concept was subsequently adopted for more products such as FX, Exotics, CDS, and became the standard workflow in the entire risk calculation process of Morgan Stanley.

   Full-Stack Engineer, Node.js, Python, Java, C#, Angular, Vue.js, .NET Framework, SQL, Spring Boot, ASP.NET, MySQL, Azure, CSS, Microservices, CI/CD, HTML, MongoDB, REST, Agile, Data Visualization, Kafka, Scala, JIRA, Redis, GitLab, NumPy, RabbitMQ, Splunk

2. Interactive Chatbot for Traders

    

   The chatbot included features to automate the tracking of important job IDs across different engine logs, monitor execution status, and provide early warnings for potential errors.
   It implemented risk alerts, limit checks, client portraits, and order execution functionalities to enhance user experience and facilitate informed decision-making, and streamlined critical job failure response by compiling and sending error/warning chains directly to group chats, enabling swift issue resolution.
   It successfully prevented a potential loss of $19 million through the chatbot’s timely intervention, demonstrating its effectiveness in enhancing trading desk operations.

   Backend Engineer, Product Manager, Java, Machine Learning, Microservices, REST, WebSocket, Microsoft Dynamics, Splunk

3. Data Milestone Project

    

   I pioneered the design and implementation of the data milestone concept for Interest Rate (IR) products in the Market Data domain, resulting in a significant increase in cache hit rates during heavy real-time risk calculations. This milestone concept was later expanded to cover a wider range of products, including FX, Exotics, and CDS, ultimately becoming a standard workflow in the entire risk calculation process.

   Backend Engineer, Azure, MongoDB, Scala, Redis

Independently built and maintained China’s largest information delivery website for ABS products www.cn-abs.com; led the development of various deal builders and analytics applications for ABS products

1. CNABS Website (www.cn-abs.com)

    

   I utilized .Net, C#, and Vue.js to develop the website “www.cn-abs.com”. The website provides internal and external users/customers with comprehensive solutions for asset securitization, product issuance, and investment analysis. Additionally, it automatically generates analysis scripts and payment waterfall model visualization web pages, conducts real-time scenario analysis, Monte-Carlo simulation, pricing valuation, and stress testing on structured product models, making it a powerful tool for investment professionals.

   Full-Stack Engineer, Product Manager, Node.js, Python, Java, C#, Angular, Vue.js, .NET Framework, SQL, Django, Spring Boot, MySQL, Azure, CSS, Microservices, Spring Framework, CI/CD, HTML, MongoDB, Kafka, Scala, JIRA, GitHub, jQuery, Redis, GitLab, NumPy, RabbitMQ, Splunk