Hi, I’m Krishna

"A code virtuoso !"

I am pursuing M.S. in Computer Science at the University of North Carolina, Charlotte, and boast over 7 years of extensive experience in data engineering, real-time applications, software engineering, and machine learning. Proficient in programming languages such as Python, Java, and Javascript, my expertise extends to cutting-edge technologies like Deep Learning and Generative AI. I have a proven history of driving substantial growth in the brokerage business at Kotak Securities Institutional Equities, and my leadership skills are acknowledged for transforming vision into tangible results. With a consistent focus on delivering high-quality work, fostering collaboration, and leveraging strong technical and business acumen, I am a valuable asset to any team.

Education

University of North Carolina at Charlotte (Charlotte, USA)

M.S. in Computer Science (GPA 4/4) Aug 2023 - Dec 2024

Research Assistant - (Emotion Classification, RoBERTa, LLM, Python, React.js)                  Jan 2024 - Current
Teaching Assistant - (AWS, Hadoop, Typedb, Neo4j, LLM and Knowledge Graphs)       Aug 2023 - Dec 2024

University of Mumbai (Mumbai, India)

B.E. in Computer Engineering Aug 2012 - Jun 2016

Work Experience

Kotak Securities Institutional Equities (Mumbai, India) : 2018-2023

Tech Stack: Python & libraries, Java, Shell scripting, Cassandra, Postgres, Redis, Kafka,
Tibco Streambase, Panopticon, PyTorch

Implemented data infrastructure, automated quantitative reports, and visualizations with Python, leading to substantial 4-hour daily time savings for traders/stakeholders and enhancing operational efficiency.
Developed real-time analytics systems and dashboards, driving a 3x increase in brokerage business, and streamlined order book management for top hedge fund clients.
Built, a back-testing framework for testing options strategies and developed strategy performance dashboards.
Created Transaction Cost Analysis to showcase algorithm performance, resulting in a 10-basis points improvement.
Utilized ARIMA and GARCH models for time-series analysis, enhancing VWAP performance by 10-basis points.
Worked on real-time stock price prediction using XGBoost and deep learning algorithms like RNN and LSTM. Researched quant trading fundamentals and market microstructure to improve algorithms.
Led a team of 7 Python developers, overseeing data analytics, automation projects, business requirements, pipeline design, and project delivery.

Tech Mahindra (Mumbai, India) : 2016-2018

Tech Stack: Java, Selenium, Shell scripting, Python, Scikit-learn

Worked on End-to-end testing of Cloud orchestration platform for AT&T and took responsibility for writing test cases and performing automation improving efficiency by 70%. Lead a team of five testers.
Developed machine learning model for predicting Go or No Go calls using algorithms like Logistic Regression and Support Vector Machines achieving 90% accuracy.