Hemangi Bachhav
Quant Analyst @Arya Risk Management Systems Pvt. Ltd
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WORK HISTORY
Quant Analyst @Arya Risk Management Systems Pvt. Ltd
Pune, IN
Applying data science, statistical modeling, and quantitative analysis to forecast energy markets and deliver actionable insights for trading and operational decisions-Develop and deploy time-series forecasting models using Python, R, and SQL for short-term and intraday power market analysis-Build machine learning workflows with probabilistic forecasting, capturing nonlinear market behavior and extreme events using Random Forest, Gradient Boosting, XGBoost, and Statsmodels-Designed a block bidding prediction algorithm leveraging historical bid outcomes and market dynamics to recommend competitive prices-Analyze daily PTP files, monthly CRR data, and annual auctions to identify pricing trends, congestion patterns, and key risk drivers, applying EDA, feature engineering, and statistical modeling-Implement backtesting, validation, and monitoring frameworks to ensure model robustness and reliability across changing market regimes-Automate data ingestion, cleaning, and analytics pipelines using Python, SQL, and SAS, enabling scalable, reproducible, and efficient decision support-Translate complex model outputs into stakeholder-ready insights, dashboards, and visualizations using Power BI, Tableau, Matplotlib, and ggplot2-Explore LLM-assisted workflows for accelerating exploratory analysis, summarization, and reporting, supporting faster and more informed decision-making.
EDUCATION
Savitribai Phule Pune University
Hsc, Science
Sir Parashurambhau College - India
Bachelor of Science - BS, Statistics
Symbiosis Statistical Institute, Pune
Master of Science - MS, Applied Statistics
ABOUT HEMANGI BACHHAV
My journey with data started out of curiosity, how a few numbers could reveal patterns, predict outcomes, and explain real-world behavior. That curiosity soon turned into a career built around finding meaning in complexity.Today, I work as a Quantitative Analyst, blending statistics, programming, and business understanding to make sense of the power market (ERCOT). From forecasting prices and analyzing bid files to building optimization models, I enjoy transforming large, chaotic datasets into insights that actually drive decisions.Before stepping into the energy domain, I explored the world of clinical and business analytics, learning how precision, reproducibility, and collaboration can make data truly valuable. Along the way, tools like Python, R, SQL, SAS, Power BI, and Tableau became my daily companions.At my core, I’m driven by curiosity, the kind that makes you question trends, test assumptions, and keep learning until the data tells a clear story. For me, analytics isn’t just about numbers; it’s about connecting logic with impact.
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