Page 56 - Carlson School GBCC Career Guide

MS in Business Analytics
RESUMES
EDUCATION
ADITYA SINGH
5555 Washington Ave S • Minneapolis, MN 55555 • 612-444-5555 • singha000@umn.edu
UNIVERSITY OF MINNESOTA, Minneapolis, MN Carlson School of Management
Candidate for Master of Science in Business Analytics
INSTITUTE OF TECHNOLOGY, Bangalore, India
Bachelor of Engineering (Honors) in Computer Science & Engineering
EXPERIENCE
CARLSON ANALYTICS LAB, Minneapolis, MN
Analytics Student Consultant
Client: Leading Hospitality and Entertainment Business
May 2020 June 2016
June 2019 – Present
• Revamped room allocation system by training ensemble model of XGBoost and logistic regression in scikit-learn on 500K+ transaction data to forecast hotel daily/biweekly demands, improving prediction accuracy rate by 30%
• Web-scrapped 3K+ online reviews using Python and conducted sentiment analysis in R to uncover occupancy rate decline
• Redefined customer worth evaluation metrics using k-means clustering and prioritized room assignment to increase usage
Client: Fortune 150 Global CPG Company
• Determined factors influencing market share using regression and created retail clusters for assortment planning
• Performed market basket analysis using association rule in R and developed effective product assignments
• Built Tableau dashboard and R Shiny app to report market insights and reduced manual efforts by 60%
• Performed root-cause analysis of anomalies in product trends to identify pain points and gain detailed market insights
Client: Business Travel Management Industry Leader
• Forecasted consumption of corporate travel market for five different Geo-Markets by building ARIMA models in R and SQL • Designed Tableau dashboard to report MoM forecasts and incorporated performance metrics in the dashboard
• Improved forecast accuracy of consumption model by 6-10% for hotel room pricing, booking volume and length of stay
• Presented data driven insights for niche consumer segments thereby assisting client in budgeting & marketing decisions
IBM, Pune, India
Associate System Engineer - Analytics July 2016 – April 2019
• Built a cost-sensitive predictive model for client Vodafone Ireland, the largest telecom company in Ireland to predict
customer churn using Python, which helped improve customer retention by 40%
• Improved marketing effectiveness of Vodafone Ireland by customer segmentation using DBSCAN clustering in R
• Built a predictive model using Random Forest in Python to precisely identify potential targets of marketing campaign for
plan Vodafone Red. The lift value of the model is 3.8 for the top 20% probable targets
• Developed visualizations and dashboards using Tableau to identify and report sales trends across various market segments
• Created BI reports using SAP BI Launchpad to track invoices for the finance department of client, NiSource, one of the
largest fully regulated utility companies in US and improved timely payment collection by 15%
• Designed SQL queries for logically separating courses and employee records in learning management system for the
separation of two companies, enabling smooth operation before physical separation of database
DATA SCIENCE PROJECTS
Text Analytics: Categorized New York Times articles using Topic Modeling and built predictive models using SVM to predict number of Twitter shares before publishing using Python and R with average accuracy of 70%
Big Data Analytics: Determined most active groups on meetup.com website using RSVPs data and identified most trending topics by categorizing similar groups into one using Spark and SparkR and visualized results using Plotly
Insight Analytics: Identified influence of population, education level, poverty and other factors on the crime rate of counties in US by building OLS model with logarithmic transformations using Python to better resource PD with insights
Predictive Modeling: Determined likely users to buy premium subscription on a music listening social networking website in the next 6-months using AdaBoost in Python on 173K records, helping in better targeting of promotional campaign
SKILLS
• Tools: R, Python, Tableau, SQL, MS Excel, Hadoop, Spark, Pig, Hive, RapidMiner, SAP BI tools, Google Analytics, C++ • Techniques: Predictive Modeling, Exploratory Analysis, Statistical Analysis, Time Series Forecasting, A/B Testing, Data
Visualization
54 Carlson School of Management