Brooklyn, New York
Phone: 5049080045, Email: firstname.lastname@example.org
Data Scientist Intern, with experience in identifying business problems to be solved with analytics, extracting useful insights from past data, developing stable machine learning and statistical predictive models using R, Python, Spark and Tableau, and extensive experience in anomaly detection using unsupervised machine learning techniques.
Programming – R, Python, Spark, Hadoop MapReduce, SQL, Hive, SAS
Machine Learning – Scikit Learn, Tensorflow, Random Forest, Decision Trees, Gradient Boosting, Support Vector Machine, Artificial Neural Networks, Clustering, Recommender Systems, Text Analytics
Data Analysis – Data cleaning and Exploration, Feature Extraction, Developing predictive models, Model selection, Model Evaluation and Metrics, Cross Validation, A/B Testing
Statistical Analysis – ANOVA, Multiple Regression, Confidence intervals, Hypothesis testing, Significance Tests
ML Azure – Data acquisition and analysis, building and deploying Machine Learning models
Data Analysis Tools – ML Azure, Tableau, MS Excel, SAS Enterprise Guide, Weka, SAP, Power BI
Financial Analysis – Balance sheet, Income statement and Cash Flow Analysis, Financial Ratio Analysis, Portfolio Analysis, Credit Risk Modeling
DATA SCIENCE INTERN
Capsule8, Brooklyn NY – May 2017 – Present
- Anomaly Detection
- Data collection from Docker Containers.
- Unsupervised and semi supervised machine learning models using R and Python.
- Built a custom classifier for anomaly detection using Clustering models (Partitioning Around Medoids, Hierarchical clustering).
- Random Forest in supervised and unsupervised mode.
- Novelty Detection and Anomaly detection using Scikit Learn.
- Anomaly detection using Tensorflow
- Conversion of R code into web API, for shipping and testing models.
Cognizant Technology Solutions, India – September 2011 – July 2014
- Experience in Software Testing Lifecycle, preparing Understanding document, Test plan and strategy, developing and executing test cases, Regression testing, User Acceptance testing
- Awarded “Exceeded All Expectations” – the highest rating in the year-end appraisal in Cognizant Technology Solutions, for logging the highest number of defects that was brought to closure.
- ISTQB (International Software Testing Qualifications Board) certified.
UNIVERSITY OF TEXAS, ARLINGTON – December 2017
Master of Science – Business Analytics – GPA: 3.7
Relevant Coursework: Advanced Business Statistics, Economic Analysis, Web and Social Analytics, Predictive Modeling using R, Principles of Business Data Mining, Big Data Analytics, Measurement and Analysis for Business Decision Making, Economic Forecasting using R, Data Warehousing.
DATA SCIENCE AND DATA ENGINEERING BOOTCAMP, Austin – January 2017
Attended a 5 Day – boot camp on Data Science, Data Engineering and Machine Learning, conducted by Data Science Dojo, at AT&T Executive Education Center at University of Texas, Austin.
SCSVMV University, India – May 2011
Bachelor of Engineering – Electronics and Communication Engineering – GPA: 4.0
DATA ANALYTICS PROJECTS
- Temporal structural model embedded in a logit framework in R, to predict whether a customer would renew the service contract with a company based on past incidents and various factors variables.
- Research for Washington Nationals: Random Forest model in R, to predict “Pitch Type”.
- Pricing and Sales Analysis for a store, based on Advertisement expenditure, Rebates and a seasonal factor for Christmas. Also developed a methodology that would easily facilitate Model Selection.
- XGBoost model in R to predict the interest level in each Rental Listing in a Real-estate
- Predicted Survival Rate on Titanic, using Random Forest in R.
- Random Forest model in R and PySpark, to predict housing prices, for a competition in Kaggle.com.
Awarded the Wayne Watts scholarship for the year 2016-2017, at University of Texas, Arlington.
Founder of INSAS (Inspirations & Aspirations) – now a flagship technical symposium of SCSVMV University, India.