****, * **** ***, ******, Colorado 80204
Cell : +1-720-***-**** e-mail : firstname.lastname@example.org SUMMARY OF EXPERIENCE
Current student at the University of Colorado, Denver pursuing Business Analytics. Well versed with SQL, Python and R programming languages. Excellent understanding of Statistics and Statistical Methods. Very good MS Excel skills.
Software experience with Microsoft Office Suite and CCH access (Deloitte tool for analytics). Developed models and carried out the analysis in R, Python and advanced Excel creating Pivot Tables, Lookups, Macros and more. EDUCATION
University of Colorado Denver, Denver, CO, 2021
Master’s in Business Analytics (MSBA), 3.95/4 GPA
Fall 2019 courses : Statistics for business analytics, Computing for business analytics and Supply chain analytics
Spring 2020 courses : Time series forecasting, Prescriptive analytics w/ optimization and Data visualization. The project work and case studies are on tools such as Tableau, PowerBI and languages such as R and SQL. SRM University, Chennai, India, 2017
Master of Business Administration, Finance, 7.63/10 GPA Analytics Projects/Cases
1. Linear regression on non-airline revenue streams at DEN: o Case study to predict future non-airline revenue such as rental cars, ground transportation, food, etc. o Carried out extensive pre-processing and EDA analysis on the data set. Added relevant independent variable (USA GDP) outside the given data set for years 2012 to 2017. o Built various linear regression models using R. Used various feature selection techniques such as Stepwise AIC and Best subset to achieve low VIF values, significant p-values and high adjusted r squared values. o Carried out cross-validation and was able to predict with an accuracy ranging from 87 - 94% for various models. 2. E-commerce - The Olist Brazilian Ecommerce Project using Python: o Carried out extensive pre-processing, EDA analysis and correlation analysis on the dataset. o Used Python packages (Pandas, Numpy, Matplotlib, Seaborn) for analyzing the data and graphical visualization. o Build various regression models and used other techniques such as kNN, statistical techniques, etc. 3. Effect of schooling on women’s fertility:
o Carried out extensive pre-processing, EDA analysis and correlation analysis on the dataset. o Built linear regression models in R. Used various feature selection techniques - Stepwise AIC and Best subset. o Performed cross-validation on the testing dataset and used K-fold cross-validation. o Build a non-parametric model – Quantile regression and models using advanced machine learning techniques such as Decision Tree, Random Forest, SVM, kNN and compared the different models. 4. COVID19 Xcel Energy Consumption Impact:
o Analyzed the average electricity consumption for 3 groups – Residential, Large Commercial & Industrial and Small Commercial & Industrial.
o Build various time series models such as ARIMA, STL decomposition, Seasonal Naïve, Neural networks, using R. o Did the model comparison and predicted the average sales for the upcoming months. Also, analysed the COVID- 19 impact on the average consumption for each of the 3 groups. PROFESSIONAL EXPERIENCE
UC Denver, Denver, Colorado, August 2019 to present o Teaching Assitant for Business analytics(BANA3000 and BANA2010) by Prof. Martin Sabo o Graduate Student Assistant for the Risk Management and Insurance Department (Financial Budgeting). Deloitte, Hyderabad, India, May 2017 – June 2019
Tax Consultant - II
Managed taxation engagements in teams located across the US and Indian sub-continent.
Analyzed GAAP based financial statements and auditing documents provided by the clients for accuracy, validity, and legalities defined by the US tax code.
Leveraged tools such as Advanced MS Excel and Go-system and CCH access (Deloitte tools) to develop forecast models for quarterly and annual estimated tax returns and annual extensions.
Awarded outstanding participant in USI Tax Client Service Readiness, new hire training program and a spot award for highly collaborative, accurate and result-oriented work.