Software Engineer, data analyst, modeling and optimization

Location:

Tempe, AZ

Salary:

75000

Posted:

June 01, 2018

Contact this candidate

Resume:

Utkarsh Agarwal

+1-602-***-**** ********@***.*** https://www.linkedin.com/in/utkarsh-msba/

Result driven analytical engineering professional with two years of experience in Agile environment analyzing data, deriving insights and creating interactive dashboards, seeking a position in analytics for performance optimization and decision making

Education

W. P. Carey School of Business at Arizona State University, Tempe, AZ

Aug 2017 - May 2018

Master of Science in Business Analytics (MSBA), GPA 3.68

Krishna Institute of Engineering & Technology, Ghaziabad, India

Aug 2011 - June 2015

Bachelor of Computer Science & Engineering,

Technical Expertise

Programming Languages: SQL, R (XGB, TS, TM), Python (SciKit-learn, NLTK), SAS Base, JavaScript, MDX

BI/Analytics Tools: Tableau, PowerBI, Excel, SPSS, SAS, IDE Python 3.6, RStudio, Minitab, Azure ML

Big Data Platform: Cosmos, Hadoop Hortonworks(Pig/Hive/Storm/Kafka), MapReduce, AWS(EC2)

Database Management: SSMS, SSIS, SSAS, Visual Studio (Scripting), Excel, MySQL Workbench, ETL

Major Area: AGILE SCRUM, Time Series Analytics, Forecasting, Trend Analysis, Cluster Analysis, Data Mining, Predictive Analytics, Analytical Decision Modeling, Marketing Analytics, Churn Prediction, Applied and Predictive Analytics, Text Mining

Academic Projects

Machine Failure Prediction: Generated clusters for finding the on-set of failure using NASA’s Machine Degradation data

Developed various Machine learning models for fraud detection, target marketing and customer churn prediction

Build a recommendation system on Amazon metadata using Social Network and Sentiment Analysis on twitter data

Visual stories through interactive dashboards using Tableau & SQL, logistic regression models using R & Python

Designed optimization models and other analytical decision models using Excel Solver Table and precision trees

Build a simulation based prescriptive model using Risk Simulation tool in Excel to find optimal number of solar panels to be installed to reduce the price of electricity generation over a period of 25 years.

33 Buckets: Used time series clustering and regression and build a recommendation model for optimal cost in select countries. This has helped them reduce the overall expenditures by 8%

Chemonics: Building distribution strategy by analyzing consumption pattern of medical drugs by various clients

Created a model to predict ratings a reviewer would give to a brand based on category level information for the reviewer using Natural Language Processing in Python using NLTK, Pandas, NumPy and SciKit-learn

Professional Experience

Software Engineer Dec 2015 – May 2017

MAQ Software (Client: Microsoft)

•Created and optimized ETL packages saving approximately 88% of server time for the client

•Optimized data cube to provide faster data processing and availability for data visuals.

•Developed dashboards for worldwide sales and marketing data using PowerBI and SQL

•Forecasted Black-Friday and Thanksgiving online and brick n’ mortar sales with an accuracy of 72%

•Created optimization model for marketing strategies helping the client boost sales by 3%

Associate Software Engineer Aug 2015 - Nov 2015

Randstad (Client: Microsoft)

•Created live reports using PowerPivot and SQL data queries in Excel

•Created interactive web forms, collected data and pipelined it to Azure database

•Created stored procedures, table indexes and wrote Cosmos scripts for big data ETL and querying

Achievements

•Wharton (UPenn.) certified Business Analytics specialist (Coursera)

•University of Colorado certified Data Warehousing Specialist (Coursera)

•Harvard University Certified Computer Science Professional – CS50 (edX)