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Data Scientist Resume

Austin, TX


Programming: Python, SQL, SciKit - learn, Numpy, Pandas, Matplotlib, Java, Web Scraper (Selenium, Beautiful soup)

Data Science: Statistics, A/B testing, TensorFlow, Neural Networks, Natural Language Processing, Linear and Logistic Regression, Classification, K nearest neighbors (KNN), Decision Tree, Support Vector Machine (SVM), Ensembling, Bagging and Boosting, GLM, Random Forest, Gradient Boosting, AdaBoosting, Clustering, Grid Search, Cross Validation

Analytics: Text and Image analytics, NLTK, PCA, K-means, Tableau, Data processing, modeling, and visualization

Computer/Databases: Relational Databases like Oracle, MySQL and PostgreSQL, Data Structures and Algorithms

Web/Cloud: Spring Framework, JSP, Google cloud platform, AWS, Jinja2, Unix, HTML



Data Scientist, Austin, TX


  • Developed a scalable machine learning workflow/framework to make deployment of ML models in production faster
  • Deployed a Machine Learning model in production using PMML, Java, and Spark to perform offline batch predictions


Data Analyst


  • Collected, Cleansed and Analyzed the structured and unstructured data which was used for major business initiatives which resulted in better strategies and the 10% increase in revenue
  • Launched Periodic Access Review s using Oracle Identity Analytics (OIA) for managers to audit access
  • Built and maintained the complex SQL queries and Python scripts for data analysis and different analytic models
  • Worked on SQL and Identity and Access Management (IAM) tools like Oracle Identity Manager (OIM) to provide users with secure, fine - grained access to enterprise resources which increased the efficiency of the teams


Java Developer


  • Developed User interfaces using object-oriented methodology and software engineering development lifecycle
  • Built an application on spring framework and Beans (EJB) utilizing agile development methodology for business logic

IT Support



  • Used deep learning techniques like Confidential and Recurrent Neural Networks ( Confidential ) to classify tickets into different categories based on their description and deploy the model on Amazon AWS and integrate with ServiceNow
  • Built a recommendation engine using spark and python applying collaborative filtering technique
  • Twitter Sentiment Analysis to analyze key factors which impact result of an election poll using NLP techniques
  • Social Media Analysis on Edmunds.com and offer advice/insights to business individuals of brands
  • Calculated expected bid price of the players for the upcoming IPL season by scraping statistical data from IPL website and calculating popularity index by tweets analysis and applied XGBoost regressor model for predictions
  • Built a website in Java, using JSP pages to build the user interfaces and JDBC to connect with Oracle Database at backend and commit changes directly to the database

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