Krishna Kumar Yadav Email & Phone Number

Austin, Tx, Us

Rock Hill, South Carolina, United States

Charlotte, North Carolina, United States

Fine-tune LLMs (GPT) for the classification of ethical leadership signals.

Charlotte, North Carolina, United States

Cloud Computing, Hadoop, Knowledge Graphs, Large Language Models (LLM), Document QA Bot (Retrieval Augmented Generation)

Mumbai Area, India

• Ideated and automated Transaction Cost Analysis (TCA) to showcase trading algorithm performance, resulting in a 20-basis points improvement in overall algorithmic trading.• Engineered a back-testing framework to validate options strategies using Python's Backtrader module and deployed a strategy performance web application in Flask, resulting in a 35% increase in options trading signals.• Conducted time-series analysis using Python, implementing techniques such as ARIMA and GARCH. Optimized the VWAP algorithm with GARCH, resulting in a performance enhancement of 10 basis points.• Managed a 7-member Python development team and collaborated with cross-functional teams in product, derivatives, sales, back-office, and research. Oversaw business requirements analysis, data analytics, software development, and project delivery, resulting in the successful onboarding of five major hedge fund clients.

Mumbai Area, India

• Designed and implemented data infrastructure, streamlined quantitative reports, and visualizations using Python, Cassandra, and Postgres. This resulted in daily time savings of 4 hours for traders/stakeholders while amplifying operational efficiency.• Coded real-time analytics systems and dashboards using Python and Java, driving a 3x increase in brokerage business.• Developed a real-time system for generating options trading signals and alerts.• Researched real-time stock price prediction for a single stock using XGBoost, yielding 55% accuracy. Uncovered quant trading fundamentals and market microstructure to optimize in-house algorithms.

Mumbai Area, India

• Spearheaded end-to-end testing for AT&T’s cloud orchestration platform, overseeing test case creation and automation, resulting in a 60% efficiency improvement.• Conceptualized machine learning models for predicting Go or No Go calls using algorithms like Logistic Regression and Support Vector Machines achieving 90% accuracy.• Managed cross-functional collaboration within an agile framework to ensure timely delivery, while simultaneously mentoring a team of 5 testers for project success.

Master Of Science - Ms, Computer Science, 4/4

Activities and Societies: Research Assistant

Bachelor’S Degree, Computer Engineering