Industrials

First IITian to receive 6 month internship in Morgan Stanley quant teamReceived full time offerRotation across 3 teams - credit risk, traded credit and market risk teams

•1/13 selected from 400+ applicants by a panel of Deans to facilitate the placement, internship &career development activities of 3000 + students.•Contacted 950+ companies individually, the highest ever by any placement coordinator of IIT Kharagpur.•Successfully convinced over 50+ recruiting firms including 30+ first-time recruiters like Halliburton IARC(Part of Blackstone Group).•Led a team of 30 department representatives to handle screening tests ,group discussions and interviews of 200 + firms in online mode for first time.

•Segregated the firms into qualified &unqualified; Identified best subset of 6 variables from 60+ variables affecting underpricing and qualification of firms.•Calculated propensity score of each firm based on the 6 variables ; Checked the balance based on propensity scores and discarded the imbalanced firms.•Performed outcome analysis by estimating difference in underpricing of qualified and unqualified firms;Cross checked the result by sensitivity analysis.

Employed meta-analysis through 327 research papers to study the internationalization of firms and business groups in India and other Asian countries, while correlating with the legal reforms and affiliation of firms and studying how firms utilize the institutional voids in foreign countries

Title of Project: Assessing the Efficiency of Assets created through MGNERGA 1.Scrapped data of the official website of MGNERGA.2.Cleaned the scrapped data for further analysis. 3.Done econometric analysis on the data collected on a particular district of Jharkhand by investigating into the questions of delay distribution of the assets created , budget allocation of the assets and thus delving deep into existing questions of corruptions.4.Cross-validating the hypothesis derived from the inference concluded from the previous district on other districts and thus concluding which months face maximum delay,which type of assets face maximum budget allocation,thus directing the government to delve deep into these matters of concern.LANGUAGE: PythonLIBRARIES: BeautifulSoup,Pandas,Numpy.