Bharat is a full stack data scientist, harvesting data from its origin in raw form to finished end product in form of insights and strategy. He is generally sandwiched between Business Strategists and Marketeers, from problem definition to insight sharing, on one side and Programmers and Data Engineers, from prototyping to deployment, on the other side. Be it conventional statistics or modern data mining algorithms, he applies what is necessary to solve the problem.
Bharat has worked on developing several commercially deployable machine learning models such as automated risk underwriting for an insurance company, financial product recommender system for a bank, airtime transfer propensity predictor for a telecom company etc.
He masters R, Python, PostGres, Tableau, D3.js etc at the highest level and works end to end from Data Engineering to Data Analysis to Data Visualization.
Bharat teaches a Quantitative Research and Advanced Multivariate Methods course to PhDs and DBAs at UUM. He is adept at Deep Learning (Tensorflow, Keras, Theano, CNN, RNN), R (dplyr, rstanarm, knitR, ggplot2), Python (Pandas, NumPy, SciPy, Bokeh, Matplotlib, Seaborn), Data Visualization (Tableau, MicroStrategy, D3.js) machine learning (Scikit learn, Weka) and Natural Language Processing (CoreNLP, NLTK, TextBlob).
