New York City Metropolitan Area
Anita is an engineering analyst at Goldman Sachs. She completed her undergraduate studies at Columbia University School of Engineering and Applied Science (SEAS), with a B.S. in computer science and a minor in economics. Anita formely interned at Goldman Sachs as a summer (software) engineering analyst in a quantitative developer role and built a historical market data service in C++ simulating live exchange feed to enable backtesting for low-latency electronic trading systems. Her research interests include focusing on operating systems scheduling and core allocation to minimize datacenter tail latency and maximize CPU utilization. Some of Anita's interests include financial technology, operating systems, low-latency/high-frequency electronic trading systems development, algorithmic trading theory, and technology for social good. She was executive lead of Columbia's annual MLH hackathon, DivHacks, and was editor-in-chief of the Columbia Junior Science Journal. In her spare time, she enjoys creative writing, tending to her plants, and cooking homemade meals with her family.
Conducted research in operating systems scheduling and core allocation to minimize datacenter tail latency and maximize CPU utilization.
Interned on the FICC (Fixed Income Currency and Commodities) Systematic Market-Making Cross-Asset Engineering team in quantitative developer role. Built historical market data service in C++ simulating live exchange feed to enable backtesting for low-latency electronic (algorithmic) trading systems.
Teaching assistant (TA) for COMS W3203: Discrete Mathematics and Graph Theory, offered by the Columbia University Computer Science Department (a CS core class and requirement for all CS majors). Hosted weekly office hours to answer students’ questions, graded problem sets and exams, and wrote recitation materials for classes of 300+ students.
Programmed in C# and used Apache Kafka for correspondence team’s document services back-end functionality to deliver annuity statements to clients. Worked in team to develop AI-driven financial news media scan trained on HuggingFace FinBERT machine learning model that can web-scrape and is integrated with Slack API to provide daily life insurance and annuities news to employees. Developed a due diligence questionnaire (DDQ) ChatGPT-esque knowledge base model tested and trained to shorten DDQ/RFI process time.