Sebastian Dounchis

About Sebastian Dounchis

Computer Science & Business Administration at Carnegie Mellon University. Incoming Quantitative Trader at Optiver Co-Founder & COO of DART (Driving Automation in Repetitive Tasks), a software-implementation startup planning to revolutionize the way workers input data and perform tasks with computers. Ex-SWE Intern at eServices Technology. Ex-President of Stock Talks and Scholars of Finance at Carnegie Mellon. I’m an incoming Quantitative Trader who is passionate about finding efficient solutions to complex problems and enjoys integrating a competitive nature in day-to-day work. I have strong technical skills from my background in CMU CS on top of the professional programming I have done for eServices Technology and DART, my start-up in the medical software industry. Through my work with clients at DART, my team projects at eServices Technology, and workshops with Scholars of Finance, I have strong professional soft skills which compound on my technical ability to provide efficient impact. As a Quantitative Trader Intern at Optiver, I excelled in an intensive options theory and strategy course. After the course, I applied this knowledge towards trading in a live market, simulated impact environment, applying strategies with live feedback on trading decisions. At eServices Technology, I restructured the SQL database, boosting data retrieval efficiency by up to 20% in select modules, and created a complex marketing campaign module that segments customer populations and sends hundreds of thousands of marketing materials over email, SMS, and physical mail. My system also provides clients live in-depth email and SMS tracking statistics on upwards of millions of marketing materials. In my work with DART, I have programmed over 60 hotkey shortcuts for use with EyeMD & IntelleChartPRO EMR software. These shortcuts increased speed by 265% and improved accuracy to 100% for clinic technicians inputting EMR data. My engineering kept the user interface easy to learn and work with for all. Recent programming projects that I have worked on include a cache memory simulator and a dynamic memory allocator in C. The cache simulator fully processed of trace files of memory writes and reads through a cache and recorded statistics of cache hits, misses, and evictions. I also created the dynamic memory allocator, using segregated doubly linked lists of free memory spaces to achieve very high throughput and memory utilization levels. Proficient: C, Python, SQL, Node.js, JavaScript, Unix, Linux, Pandas, Excel Knowledgeable: C++, C#, Java, R, NumPy

Experience

1. Incoming Quantitative Trader

   Optiver

   Aug 2024 — Present · Chicago, IL, US

Education

• Carnegie Mellon University

  Double Major: Computer Science and Business Administration