SANGAMESH INAMDAR

Orlando, FL – ***** 407-***-**** adhzgf@r.postjobfree.com LinkedIn

● A Data Enthusiast with 4+ years of Industrial experience in Data Analytics, Predictive Analytics, and Analytics Consulting with deep knowledge of Analytical Techniques

● Extensive hands-on experience using Big data tools including Python, SQL, R, SAS, PySpark, Tableau EDUCATION

Master of Science in Data Analytics University of Central Florida, USA May 2020 Course work: Statistical Methods & Modeling, Machine Learning, Data Mining, Data Visualization MBA (Quantitative Techniques in Business & Finance) University of Delhi, India May 2015 Course work: Business Statistics, Econometrics, Time Series & Forecasting, Corporate Finance, Marketing Bachelor of Engineering Visvesvaraya Technological University, India June 2012 TECHNICAL SKILLS

Analytical Tools: Python (Pandas, Matplotlib, Numpy, Scikit-learn), SQL, R, SAS, PySpark, Tableau Excel, SPSS, Google Analytics, Minitab, MATLAB, Stata Functional Skills: Predictive Analytics, Logistic Regression, Decision Trees, Random Forest, Clustering Machine Learning, Text Mining, Time -Series models, Hypothesis testing, A/B Testing WORK EXPERIENCE

Data Analyst Accenture Services Pvt Ltd, New Delhi, India (Mar 2017 – Aug 2018)

● Leading Client calls to understand the business problem, collaborating with internal teams, applying Statistical techniques to provide different Data driven solutions for various Business Problems

● Predicting Default on Future Payments - Used Logistic Regression to build Behavioral Scorecard to identify telecom customers who would default on their future payments, helping client to save more than 60,000 Kuwait Dinar

● Analysis of Marketing Campaigns - Measured the Performance of five different Marketing Campaigns using Key KPI Indicators and conducted Statistical Tests to validate the hypothesis (For US Telecom) Senior Executive Quatrro Global Services Pvt Ltd, New Delhi, India (Jun 2015 – Feb 2017)

● Fraud Detection - Used Decision Tree algorithm to Predict fraud in Credit card transactions by building set of rules and successfully reduced the Bad Block rate from 13% to 8% (For Tier1 US BANK)

● Predicting Chargeback - Minimizing the loss due to chargeback for an e-commerce merchant by developing a Naive Bayes model to classify transactions as fraud and genuine

● Mining the Credit Card customer data to derive meaningful Business insights, Customer segmentation, RFM analysis helping the client to increase revenue by 2 million dollars ACADEMIC PROJECTS

● Instacart Market Basket Analysis using Apache Spark: Mining the data to discover purchasing pattern, frequency of orders placed, products bought together. Using FP-growth algorithm generated association rules to identify top products likely to be purchased together

● Stock Market Forecasting using Time Series Analysis: Built ARIMA, GARCH, and T-GARCH models to predict future values of the stock index with later model giving lowest test error of 12%