Our client is CITI back. I am leading full-revel tech team.Key Projects:1. IMA (Internal Models Approach):In this project we do analysis of fund management and diversify them into asset classes where the bank should invest. It involves the prediction of future valuation of investment and risk calculation using HVaR (Historical Value at Risk) and RTPL (Risk theoritical profit and loss).Responsibilities:• I am mainly involved in risk calculation and risk-factor analysis.• Skills: Python, Pandas, NumPy, Shell Script, Data Analysis, Investment Banking domain knowledge.

At Vchip Technology, I have responsibility of both technical and management work.Key Projects:1. Vchip-Edu: ERP and LMS for educational instituteOn Vchip-edu platform (https://online.vchipedu.com), any educational institute/classes can start their online classes within 15 minutes. Also they can access the details of their students in single click.Responsibilities:• Back-end development (database operation) for both web-application and android app.• Built environment and maintaining application on AWS (EC2 instance)• Developed chat-bot• Skills: Laravel, TensorFlow (RNN algorithm), Keras, SQL, JavaScript, React-Native.2. Vchip-Agro: Crop MonitorIn crop monitor project, at first vchip team do the testing of soil. To reduce the number of sensors, we studied on patterns accursed in images taken by drone and applied ML algorithm to predict the moisturizing lever and pH value.Also, we monitor the growth of crop using drone in different farms and on the basis of data analysis we give suggestions to farmers about which crop and fertilizer are better for their farm to increase the productivity.Responsibilities:• Collecting data from sensors and covert it from analog to digital data and store.• Modeling and hyper-parameters tuning.• Skills: Data Mining, TensorFlow (CNN algorithm), Keras, Matplotlib, SQL, Python, Computer Vision.3. Vchip-Agro: Protect From AnimalsNow day animals are biggest hazard for farmer. In this project, we study the pattern of occurrence of animals in same farm and in different farm. We detects animals during flight time of drone using computer vision. Also, we predict the presence of animal (when drone is not in flight mode) by comparing crop damage as compare to previous flight image. On the basis of that we predict the probability of occurrence of animal on that particular day.Responsibilities:• Generate different pattern to run away animals from farm.• Use computer vision to detect animals and finding damages of crops.

Teacher Assistants under Prof. Dhrubes biswas.