About

Narendra Khichar is a highly skilled Senior Backend Developer with extensive experience in software development, machine learning, and algorithmic trading. Currently working as a Software Engineer at indmoney, Narendra is responsible for integrating 3rd party APIs for trading and implementing Redis In memory caching with ttl mechanism for static data of stocks. He has also developed OMS using GORM and push notification service based on live status of trade. Narendra's expertise in software development is reflected in his past experiences as a Software Engineer at indmoney, where he built Python programs to calculate market Momentum indicators, Trend Indicators, Volume Indicators, and Volatility Indicators from Open-Low-Close-High data of stocks. He also developed ML-based stock baskets from indexes like Nifty50, Nifty100, Nifty200, etc. and evaluated their performance with benchmark on various financial features. As an Algorithmic Trader at atraxia, Narendra developed models for multivariable time series forecasting using Tick by Tick Historical Data of last 1 year to predict Market movements, share price limit, and volume limit based on Deep Learning and neural network models like MLP, RNN CNN LSTM, and LS-SVM. He also prepared algorithms to find shares to trade every day based on their various features like volatility, liquidity, volume fluctuations, etc. Narendra is a graduate of Indian Institute of Technology, Kharagpur, with a degree in MECH.ENGG. MANUF.SCIENCE & ENGG. (M.Tech Dual 5Y). He also holds a High Secondary degree in Chemistry, Physics, Mathematics, English, Hindi from Gudha Public Sr. Sec. School, Gudhagorgi, Jhunjhunu, Rajasthan, and a High School degree in Mathematics, Science, Social Science, English, Sanskrit, Hindi from Vageswari Secondary School, Ratangarh, Rajasthan. Narendra's technical skills include Software Engineering, Backend, AWS, Python, SQL, Django, ML, test, QA, Redis, Kafka, Web, SVM, CNN, RNN, Deep Learning, Neural Networks, Jenkins, and Golang. He has relevant experience of 0.95 years and is always eager to learn and work on new technologies.