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Sr.quantitative Analyst Resume

NyC

PROFILE

  • Senior quantitative Modeling analyst and with strong record of collaborative problem solving and innovation.
  • Integrates cutting - edge statistical and machine-learning methods with macro and company data to improve investment-risk performance.
  • Broad experience in multiple asset classes.

TECHNICAL SKILLS:

Econometrics: Time Series Analysis, GARCH,Regression. Monte Carlo Markov Process

Data Science: Machine/Deep learning, NLP, Bayesian Analysis.

Fixed Income: Derivatives(Equities,Exotic,Interest Rate),Equities,FX Derivatives/Options, Structured Products, Credit Derivatives, Counter party Credit Risk, Market Risk Numerical Methods,Stochastic Calculus, Optimization.

Programming: Python, Py-spark, R, Unix,Github,SQL,KDB

PROFESSIONAL EXPERIENCE

Sr. Quantitative Analyst

Confidential, NYC

Responsibilities:

  • Enhancement and calibration to market data of pricing models for Exotic Interest Rate Derivative models(Trigger Swaps, Bermudian,LIBOR-in-arrears etc)
  • Estimation of Price Sensitivity of MBS,Corporate Bonds and other structured products due to T-Curve shifts using PC-duration( PCA) based on daily returns of these securities.
  • Development of Value at Risk analysis using Key Rate Durations
  • Calibration of interest rate models( SABR-HW, BDT etc)
  • Development of Models for credit Derivatives(Credit Link Notes, Total Return Swaps)
  • Enhancement of Credit risk modeling (PD, LGD, and EAD) for derivatives
  • Enhancement of counter party risk models (PFE,EPE,XVA), including Probability of Default and Credit Exposure and CVA
  • Development of Duration frame work for default prone securities.
  • Development of Forecast models for interest rates, Mortgage Rates based on macro economic variables for CCAR and DFAST using Statistical methods( Regression, Time Series) as well as machine & Deep learning (Random Forest, SVM,LSTM, MLPs)
  • Creation of new Volatility forecasting using GARCH- and Time Series
  • Development of Analytical models for Corporate Treasury - liquidity risk (Option Deposit Models) and interest rate risk management, cash & collateral management (Deposit Runaways), funding optimization and allocation

Sr. Quantitative Analyst

Confidential, Jersey City, NJ

Responsibilities:

  • Development of models with applied PnL Simulation methodology for different Stress testing scenarios on Government Security division(GSD) based portfolios
  • Conduction stress testing on VaR Models using PCA for MBS and ABS based Portfolios

Sr. Quantitative Analyst

Confidential, New York, NY

Responsibilities:

  • Development of Models for estimating Potential Risk exposure at the corporate account level for ETFs based portfolios and portfolios involving penny stocks by modeling volatility.
  • Perform analysis on Portfolio Re-balancing ( Smart Beta) and risk analysis (VaR, CvaR),
  • Development of Models for constructing Optimal Portfolio using Factor Models and Momentum strategy.
  • Creating Multi factor models for Equities, Confidential Barra and Factor models.

Quantitative Analyst

Confidential, New York, NY

Responsibilities:

  • Calibrating Derivative pricing Models (Equities, FX, Volatility(Heston), Futures,Swaps,Exotics) using Monte Carlo
  • Creating models for Estimation of Expected returns based on Volatility Surface.
  • Performing Multi-Asset portfolio optimization and risk analysis.
  • Calculating Estimate Exposure in Equity/FX derivative trading based on Greeks.
  • Estimation of Volatility risk in Equity options.

Quantitative Analyst

Confidential, Summit, NJ

Responsibilities:

  • Development of models for term structure shift in yield curves using PCA for price movements of Interest rate Instruments
  • Development of Models for analyzing price changes based on interest rate movements in Bond Markets.
  • Creation of Risk Frame work for multiple assets.

Electrical Engineer

Confidential

Responsibilities:

  • Development of Software systems for Loss minimization of Electrical Grid Systems
  • Creation Models for Optimization of Industrial power usage using PSO, Genetic Algorithm,Simulated Annealing

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