Quantitative Research Analyst at AN Quantech LLP with expertise in backtesting, optimizing, and deploying trading strategies. Skilled in developing infrastructure components like Position Management Systems (PMS), Order Management Systems (OMS), and Margin Management Systems (MMS). Experienced in working with both directional, rule-based trading strategies and delta-neutral, non-directional option selling strategies. Proficient in storing and processing high-frequency stock and F&O data using MongoDB, supporting robust data-driven decision-making.

Responsibilities - Conducted extensive data analysis, backtesting, and optimization of trading strategies using Python, SQL, and MongoDB that resulted in improved risk-adjusted returns and reduced drawdowns.- Deployed both directional and non-directional strategies such as Short Straddle, Short Strangle, Calender spread, and Call back ratio spread on the live market (Nifty 50 and Bank Nifty).- Researched and implemented new quantitative methods using ML techniques like PCA and Deep recurrent neural networks to predict the implied volatility of the market for the next time stamp.- Collaborated with other quants, traders, developers, and stakeholders to deliver high-quality solutions and insights for various projects such as portfolio optimization, market microstructure analysis, and trade execution optimization.

Research Topic:1. Multi-step ahead time series forecasting for network load dataset using machine learning and deep learning models.

Project Name: Speech technologies for Indian languagesProject ID: IITM/Meity/AD/369- Development of Spoken language identification system from the conversational speech of Indian languages and Indian English- Development of Dialect Identification System- Development of Language Diarization System

Project Name: Classification of sonar signals using deep convolution neutral networksProject ID: IITM/DRDO/PR/267Sponsoring Agency: DRDOPrincipal Investigator: Dr. Padmanabhan Rajan (PI), Dr. Dileep A.D (Co-PI)

Project Name: Design of Advanced Big Data Analytics in the CygNet Management System for large telecom networksProject ID: IITM/MHRD(UAY)/AD/115Sponsoring Agency: MHRDPrincipal Investigator: Dr. A D DileepRole: 1. Acquire, Pre-process and clean data, Initial data investigation and exploratory data analysis. 2. Design ML models for classification tasks and Time series forecasting. 3. Deploying ML models in production. Experience:1. Data pre-processing and exploration using various Python libraries - Pandas, Numpy. 2. Data visualization and exploration using Matplotlib, Plotly and Seaborn. 3. Building ML models using Scikit learn, Tensorflow and Keras. 4. Deploying ML models on server using flask.