Eva Wang

M.S. in Computational Science | Seeking a Software Engineer role

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I’m a current master’s student at UCSD majoring in Computational Science (CS & Math). I'm looking for a job as a Software Engineer or Quant Developer position. I have a few years of hands-on work experience in startup and FinTech as SDE (full-stack web dev) and Quant Developer (especially for derivatives). At UCSD I have research experience at Drone Lab. This lab focuses on computer vision and robotics and I joined the algorithms group, mainly working on object detection and segmentation. Before UCSD I was responsible for trading strategies as Quant Developer at a FinTech hedge fund startup. I also had training experience in Morgan Stanley Student Camp in High-Frequency Trading (HFT) group, mainly studying market-making strategies and financial microstructures.


Work Experience

Research Assistant

DroneLab - Qualcomm Institute | 2019 - 2020

Researched on computer vision area at Prof. Falko Kuester’s CHEI DroneLab.

  • Segmantation and computer vision algorithms.
  • Imaging processing and 3D Reconstruction from multi-views.

Software Engineer

ViaX Tech Online Education | 2019 - 2019

Used React.js, Node.js, Express with GraphQL, MongoDB to build web applications and deploy on AWS.

Code Reviewer

Udacity | 2016 - 2019

In the Machine Learning Nanodegree (MLND) group in China team.

  • Reviewed and guided students’ projects to complete machine learning nanodegree programs.
  • Tested and maintained the database warehouse for DiDi-Algo competition platform.

Quantitative Developer

Huidi Investment - Hedge Fund Startup | 2015 - 2016

Joined the startup as the 5th employee.

  • Built models for portfolio hedging, optimization and pricing forecasting. Researched on high-frequency and interdays trading stratgies, and risk management.
  • Contributed and developed our own internal trading simulation system based on real-world queuing systems and various orders to track order flows.

Quant Trainee

Morgan Stanley | 2015 - 2015

3-month training in High-Frequency Trading (HFT) group.

  • Researched market-making and inventory strategies, Poisson process, order-flows, and spread trading, tick-to-trade measurements, and simulations.
  • Predicted the mid-price and spread by utilizing machine learning with low latency and calibrated dealers’ indifference valuation and bid-ask quotes to narrow down the inventory risk.

Projects

Web Developer Bootcamp Projects

Open Source

Used React.js, Node.js, Express, GraphQL, and MongoDB, SQL to build payment app and Yelp-like app.

Recommendation Systems

Open Source

Products size fitting recommender systems using collaborative filtering on public datasets.

Market-Making Trading Strategies on Limit Order Books

Open Source

Modified ACD-GARCH model, considered Poisson processes, modeling on individual dealers’ optimized bid-ask trading strategies for narrowing risk based on high-frequency financial data.

Information

Publication & Research Reviews

  • 2017 · AAAI-17 Monte Carlo Localization: Efficient Position Estimation for Robots, Synced Technical Reviews.
  • 2016 · Autoregressive Conditional Duration with Generalized Autoregressive Conditional Heteroscedasticity model (ACD-GARCH) for Irregularly Spaced High-Frequency Financial Data, Master’s Thesis (Outstanding Honor).
  • 2015 · Empirical Research on the CSI300 Futures GARCH-VaR Risk Management, Modern Economic Information.

Activities & Leadership

Delivered presentations as an invited speaker at

  • 2017 · WTM Women Techmakers, Google Developers;
  • 2018 · Women in Tech, organized by the Columbia Center in Beijing.