Bio

I have a Masters degree in Operations Research from UT Austin. I specialize in Machine Learning, Data Mining, and Statistical Modeling. I have more than 3 years of experience developing programs in Python and R, and several projects in the domain of Unsupervised/Supervised Learning, Time Series Forecasting, NLP, Neural Networks, Class Imbalance problems and Data Analytics. I am currently with Finicity (a part of MasterCard). Previously, I was with JP Morgan, New York as part of the model review group. Previously I was with SparkCognition, an AI start-up, as a Data Science Intern and was working on developing computer vision models for drone thermal imaging. Prior to that, I interned at WorldQuant, a hedge fund, where I built financial dashboards for the trading team and restructured their forex hedging algorithm to potentially save $1 Million per quarter. With strong technical skills in Python, R, SQL, and Tableau and significant experience developing predictive models, I believe that data science can change the world and make it a better place! Have worked on datasets from 1000 rows to 100+ GB. Programming skills: Python[Pandas, Dask, Numpy, Scipy, Scikit-learn, tensorflow], R [caret, forecast, ggplot], MATLAB, SQL, SAS, WEKA, Tableau, STATA Machine Learning: Regression (Linear, Logistic), Clustering, Classification (SVM, Random Forest, XGBoost), Feature engineering, PCA, Neural Networks, Decision Trees, Bagging, Gradient boosting Statistics: Hypothesis testing, Time series analysis, A/B testing Areas of Interest: Python / R for Data Analysis, Statistical Modeling, Operations / Supply Chain, Financial Risk Management, Deep Learning Things that excite me: 1. All things Data! All things Statistics! 2. Technology start ups that are solving real world problems 3. Social entrepreneurship focusing on societal inclusion