May 2021 – Jun 2022 · 1 yr 1 mo · Gurugram, Haryana, India

• Part of Economic Advisory team, worked on linking ESG and other financial KPIs of a company with TSR using statistical models.
• ESG Impact Model - Econometric model linking different financial KPIs like profitability, growth, solvency etc. and ESG parameters (E, S, G and combined ESG) with the Total Shareholder return of the company.
• Researched and understood the methodology used by different ESG rating providers
• Worked on econometric model linking the different financial ratios of a company and building the isoquant curves to suggest key ratios for the companies to focus on
• Presenting the output in the form of a customizable PowerBI dashboard

Jul 2018 – May 2021 · 2 yrs 10 mos · Bengaluru, Karnataka, India

• ● Developed regression/PCA based models to explain the short term implied volatility of major equity indexes against gamma factors.
• ● Gathering and Analyzing big data using banks API and Bloomberg API and automating the existing excel based models and VBA Macros
• ● Used Tree Based models to represent correlations among the volatilities of key asset classes using Techniques like Minimum spanning trees.
• ● Data visualization using Python packages like networkX, plotly and Bokeh.
• ● Price vanilla and semi-exotic derivatives and back-test new ideas using python language

Jul 2015 – Jun 2018 · 2 yrs 11 mos · Noida Area, India

• ● Supporting various clients – Hedge Funds, Asset Managers, Endowment Funds and Insurance Companies on the Quantitative Research and Data Analytics requirements.
• ● Researched on finding the lead-lag indicator among the asset classes of loans, equities and bonds by utilizing the Machine Learning technique of hierarchical clustering, k-means, graph technique like minimum spanning tree, dendrograms along with various measures of correlations like spearman, pearson and kendall
• ● Credit card fraud detection in the transactional dataset using predictive models.
• o Performing exploratory data analysis and preparing a balanced dataset
• o Eliminating insignificant variables via statistical analysis
• o Training various machine learning algorithms like logistic regression, KNN, SVC and Random vector classifier. Fine tune the model to improve training model using performance metrics like ROC, confusion matrix.
• ● Used different techniques like regression, PCA, co-integration etc. to build models and back-test them to generate tradable strategies
• ● Worked on developing generic Quant Solutions (excel-VBA and Python based product) addressing back-testing needs of the clients. Developed following modules under the solution:
• o Momentum, Pair Trade, Quantamental (Factor Strategies).

Aug 2014 – Jun 2015 · 10 mos · Chennai Area, India

• o Valuation and analysis of vanilla, structured and exotic products and their PnLs.
• o Liaise with Trading, Financial Markets quantitative developers and Valuation Control analysts, to ensure speedy review and validation of new models and methodologies.
• o Calculation and analysis of reserves and supports the development and implementation of new reserving methodologies.
• o Production of monthly pack which clearly states the over or undervaluation as compared to Front office.
• o Escalate pricing issues, valuation parameters or instrument types that may require particular attention with critical analysis of the risks involved.

Oct 2011 – Feb 2014 · 2 yrs 4 mos · Gurugram, Haryana, India

• ● Supported a Quant Hedge fund, reading academic papers and advising the client on perspective Strategies
• ● Strategy on the concept of Residual Momentum in equities:
• ● Worked on Mean Reversion strategies on Equity and CDS indices
• ● Worked on Term Structure (identifying Backwardation and Contango) and Momentum strategy in Commodities

Oct 2010 – Sep 2011 · 11 mos · Gurugram, Haryana, India · On-site

• Worked in the Fixed Income Analytics (Structured Finance) Department of FMA (Financial Management Advisory).
• Effectively examined trustee's monthly and quarterly payment reports consisting of limitation tests, portfolio activity and
• collateral quality tests.
• Valuation and loan level analysis of Structured Products (CMBS, CRE-CDO) primarily backed by US Commercial Real Estate.
• Calculated and reviewed priority of payment numbers for Payment Dates.
• Reviewed and monitored portfolio asset ratings.