Education
Madras School of Economics
Master of Arts in Applied Quantitative Finance 2023 – 2025
Indian Institute of Technology Madras
BS in Data Science and Applications 2024 – Present
Central University of Tamil Nadu
Bachelor of Arts in Economics 2020 – 2023
Experience
MicroSave Consulting (MSC) | Research Intern
UNDP – Climate Adaptation Finance Study
  • Designed a multi-criteria district prioritisation framework for a UNDP-commissioned study, scoring 50+ districts across hazard, exposure, vulnerability, and adaptive capacity indicators to guide field selection
  • Mapped climate finance flows and scheme-wise expenditure across Jharkhand and Odisha; benchmarked state plans against national/global frameworks to identify adaptation financing gaps
  • Built QGIS visualisations for district shortlisting and block-level outputs across districts, directly informing final site selection decisions
Portfolio Stress Testing & Net Zero Strategy
  • Fed an MFI stress-testing model with district-level risk indicators, built by OCR-digitising government PDFs and Python-scraping 200+ media reports, to simulate loan losses under multiple climate hazards
  • Quantified Scope 3 GHG emissions across all applicable categories for MSC's net zero strategy, delivering findings as a client-ready presentation deck
Projects
Time Series Forecasting | R, ARIMA/SARIMA, ADF Test, ggplot2
  • Built an ARIMA forecasting model on 5 years of SpiceJet price data; performed stationarity testing (ADF), differencing, and ACF/PACF-based model identification
  • Evaluated model performance using RMSE and MAPE, presenting forecast diagnostics and residual analysis as part of an academic study
Regional Climate Cooperation Analysis | Climate Policy, Integrated Assessment Models
  • Used the RICE-2013 model to compare cooperative vs competitive climate strategies among the US, EU, China, and India; cooperation lowers emissions and slows warming, but benefits remain uneven
  • Suggested fairness measures such as technology sharing and climate finance to sustain long-term cooperation
News Sentiment and Stock Direction Prediction | Python, pandas, BeautifulSoup, scikit-learn
  • Built an end-to-end pipeline combining news sentiment with historical stock data to predict next-day price direction for Reliance Industries using multiple ML models
  • Collected and processed 8,000+ financial news articles via web scraping, engineered sentiment and market features, and evaluated models using cross-validation and precision/accuracy metrics
Certifications
Open Course in Public Policy | Takshashila Institution
Python 101 for Data Science | Cognitive Class, IBM
R for Data Science | Cognitive Class, IBM
Advanced SQL | Kaggle
Technical Skills
Languages: Python, R, Julia, SQL, LaTeX
Machine Learning: Regression, Classification, Clustering, NLP algorithms
Data Analysis & Visualization Tools: Power BI, Google Looker/Data Studio, Stata, MS Excel