OBJECTIVE

Jithendra Macha

New York City, New York

ad3oyg@r.postjobfree.com 469-***-****) https://www.linkedin.com/in/jithendra-macha/ A Highly motivated Quantitative Analyst with 4+ years of experience with comprehensive Statistics modeling and implementation skills and in-depth knowledge of quantitative finance Including Credit Risk and Market Risk models, such as Default models, Regression, and classification Models. EDUCATION

Stevens Institute of Technology, School of Business August'2021 – August’2022 Master of Science in Financial Mathematics (GPA: 3.9/4.0) Relevant Courses: Python for Finance, Machine Learning in Finance, Financial Risk Management, SAS, applied statistics, Time series analysis, Linear Regression, Financial data science, Options and derivatives, Bloomberg Terminal Acharya Nagarjuna University April’2009 – March’2012 Bachelor of Commerce

Relevant Courses: Finance, Commerce, Statistics, Accounting, Computers, SQL, Risk Management in Banking. SKILLS

Programming: Python, R, SAS, SQL

Software & Tools: MySQL, Microsoft Suite (Excel, Word, PowerPoint), Tableau, Power BI, SAS, RStudio, Colab, Jupyter, Mathematics: Probability Theory, Machine learning algorithms, Regression & classification and Time Series models EXPERIENCE

State Street Bank and Trust October’2022 – Present Quantitative Risk Analyst Boston, MA

• As part of Basel Annual Assessment, Recalibrated the Financial institutions(FI), Corporate(Corp) and Covered Bond(CB) LGD Models.

• Analyzed historical data to identify downturn periods and their impact on LGD.

• Analyzed the Single-family data and Multi-family data for Haircut computation for the CB Model.

• Developed downturn parameters that adjust LGD estimates for economic downturns.

• Conducted RWA analysis to ensure that the bank's capital requirements are adequate to cover the risk of loss given default.

• Worked on end-to-end model validation of the Wholesale Credit Risk models for CCAR, CECL- and IFRS 9 across different lines of business.

• Conducting meetings with SMEs and taking their inputs during the Recalibration processes.

• Participated in Running the PD/LGD Models during the CCAR and CECL runs and creating the Evidence folder and control process review analysis.

• Preparing the Implementation Plan(IMP) and ongoing Monitoring Plan(OMP) and submitting the Recalibration package for Validation purposes. Profitmart Securities June’2015 – July’2020

Quantitative Analyst, Investment Management Guntur, India

• Developed and implemented market risk models for various financial instruments, including stocks, bonds, and derivatives using PYTHON.

• Used historical data and Monte Carlo simulations to generate market risk estimates.

• Communicated market risk results to senior management and other stakeholders.

• Stayed up-to-date on the latest market risk modeling techniques and technologies.

• Successfully presented market risk models to senior management and other stakeholders. ACADEMIC PROJECTS

Stevens Institute of Technology

Time Series Analysis and Forecasting Using QWIM (Skills: Python, Statistics) Spring 2022

• Analyzed correlations between ETFs leveraging market price returns, mean time series modeled residuals, and mean-variance time series modeled residuals deploying ARIMA and GARCH models.

• Created and back-tested trading portfolios operating optimized pair trading techniques with favorably correlated pairs.

Market Risk: Built VaR and Expected Shortfall Model and Backtest it (Skills: Python, Statistics) Fall 2022

• Formed 3 investment portfolios and estimated volatility by operating GARCH (1,1). Calculated 1 day 99% VaR (Variance-Covariance & Historical Simulation) and 1 day 99% C-Var to determine potential portfolio losses.

• Back-tested the VaR model and documented results. Realized Risk-Adjusted Return on Capital (RAROC) on all 3 portfolios.