|Skills||Experience||Total Years||Last Used|
|SQL,SAS,Data Analysis,R, Machine learning|
Identified process boundaries and determined opportunities to automate processes and functions
Manipulated data using pivot tables, pivot charts and macros.
Boosted company efficiency and customer satisfaction by streamlining processes deemed inefficient
Conducted activity-based analysis of business processes and made recommendations based on the findings
Documented process flows and developed requirements for functional improvements and enhancements
Tracked, analyzed and interpreted trends in [Data type] data.
Developed metrics used to determine inefficiencies and areas for improvement.
Reduced organizational operating costs by [Number]% by streamlining processes
Analyzed ratings and programming features of competitors to evaluate the effectiveness of marketing strategies.
Gathered and analyzed performance metric data.
Coursework in [Course Name]Emphasis in [Name of Emphasis]
Data Analysis - SQL, SAS, R, SPSS, Advanced Excel, MySQL
*Statistics and Machine Learning- Exploratory Data Analysis, Hypothesis Testing, Linear Regression, Logistic Regression, Classification, Decision Trees, Clustering, Neural Networks, Deep learning, Ensemble modeling, Random Forest
*Business Intelligence-Tableau, MS SQL Server, MicroStrategy, Business Objects, Relational Databases
Avnet Inc.: Applying optimization to improve global cost efficiencies, capital savings through planning and resource utilization.Maximizing revenue models by minimizing travel, entertainment and logistics expenses.Modeling and simulating small improvements that would make a significant impact to the bottom line.On-site, Capstone project] PayPal Mafia: Developed SQL database for each founders' information to study commonality, interdependencies, interactions and relationships in data sets with simple scripts, algorithm and statistical inference IBM Watson The Great Mind Challenge 2014: Participated and developed a machine learning algorithm using IBM SPSS Modeler to assign TRUE/FALSE labels to question/answer pairs with an accuracy of over 90% Kaggle-Amazon Employee Access Challenge: Built a model to predict employee's access given his/her job role by minimizing the human involvement to grant or revoke employee access with 80% accuracy using various data mining classification techniques Hourly Wage Analysis: Engineered models conducting multiple regression using SAS to explain about 70% of the variation in hourly wages of workers and also investigated the key drivers like education, experience and gender that drove hourly wages.ad, automate, benchmarking, Business Intelligence, Business Processes, C, competitive, credit, decision making, financial, marketing, modeling, Oracle database, Developer, predict, pricing, processes, Process Improvement, progress, Requirement, Risk Assessment, safety, SAS, SQL, strategy, underwriting, VBA
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