Hi, I'm a Master of Science graduate in Computing (M.Sc. by research) from Queen's University, Canada.

For my thesis, I reverse engineered the natural language in the MD&A section of company SEC filings (using different learning algorithm techniques) and presented a plausible method that answers how financial statement fraud perpetrators can *unknowingly* leak deceptive signals into the narrative section - especially in a setting where multiple innocent participants contribute to its writing. I also performed a comparative analysis of several deep learning techniques for mining fraud from MD&As - the transformer model that I built achieved new state-of-the-art detection results. I was able to carry out this research under the guidance of my supervisor - Dr. David Skillicorn.

My primary skill set is in building coherent and reliable machine and deep learning models in the fintech/business space. Before Queen's, I was Data Scientist II @ Dun & Bradstreet working on credit risk analysis problems. Please find more information on my background on the Resume page. Here is my GitHub profile where you can check out some cool projects. You can also connect with me on LinkedIn.

I'm actively exploring full-time data science or machine learning roles in Canada and the US. If you are a recruiter or otherwise, please get in touch at sachin.vs@queensu.ca