Anmol Bharaj Email & Phone Number

Seattle, Washington, United States

• Leading the development of a python-based system for the automation of performance reporting for FX portfolio with a goal of eliminating daily manual kick-off of various performance analytics and reporting functions.
• Collaborated on building interactive dashboards to calculate, analyze, and visualize attribution-based performance of investment products to internal portfolio teams and executive committee

Greater Atlanta Area

• Part of the Global Risk Analytics division, contributing as a part of the Consumer Risk Modeling and Delivery team
• Responsible for the development of an interconnected model system that facilitates credit loss forecasting, as a part of the Consumer Risk Model Implementation team
• Migrated C++ code to high performance python, providing a system free of dependency on a development environment without a loss in computation time
• Optimized and parallelized the calculation workflow for the model by designing a dependency-aware job scheduler using Directed Acyclic Graph
• Implemented concepts of metaprogramming to generate dynamic python classes
• Built data pipelines to engineer and ingest data from disparate Authorized Data SourcesTech Stack: Python, C++, PySpark, SQLite, Git, NetworkX

Greater Atlanta Area

• Part of the Quantitative Finance division under Treasury, contributing as a part of the Strategic Assets and Liabilities team
• Partnered with senior management in the Quantitative Finance team to support analytics for Treasury and Chief Investment Office’s funding desk by communicating daily portfolio performance and optimal portfolio selection
• Remodeled P&L attribution using Python and PERL for the CMBS sub-portfolio and overhauled the CVaR sensitivities replicating portfolio model using cross validated LASSO for parameter selection resulting in decrease of.
• Debugged and added stability to CMM FRA lattice calibration for the purpose of increasing robustness and to account for unexplained large values in the down rate scenarioTech Stack: Python, PERL, SVN, UNIX, Scikit-learn

Gurgaon, India

• Delivered end-to-end implementation of IFRS9 impairment models and forward-looking Expected Credit Loss (ECL) models for wholesale portfolios; facilitated calculation of Economic Capital and Expected Shortfall
• Automated the process of furnishing detailed reports with analysis of areas of risk concentration, attribution of ECL based on risk factors (PD, LGD, Maturity, EAD and correlation to market) and Expected Impairment.
• Performed scenario-based stress testing and sensitivity analysis to the credit risk factors for the banks’ portfolios
• Working knowledge on multiple proprietary Moody's Risk products which include IFRS 9 and CECL impairment calculation- ImpairmentCalc and portfolio economic capital product- RiskFrontier

Pune Area, India

• Worked under Dr. Anindiya Goswami on Simulation of Stock Prices following Stochastic Volatility Models. Studied the application of the Stochastic Calculus in Financial Mathematics and Derivative pricing.
• Furnished a comparative study of the change in the prices of European Call Options against different Exercise prices with the addition of a Stochastic Volatility factor. The Black Scholes model was compared to the.

New Delhi Area, India

• Worked with a team of the Commercial Directorate of the Steel Authority of India Limited (SAIL) to perform an analysis of Steel Consumption in India by various Industries as well as prediction of Steel Consumption.
• Supported in the development of a regression based model which estimates the upcoming steel consumption based on macroeconomic data from 1992 to 2014. Performed Single Factor Analysis and Multi Factor Analysis for.

Master Of Science - Ms, Quantitative And Computational Finance

Bachelor Of Technology (B.Tech.), Mathematics And Computer Science

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