Data Analyst
Resume:
APOORVA KAMSHETTY
**************@*****.*** 404-***-**** https://www.linkedin.com/in/apoorva-kamshetty
PROFESSIONAL SUMMARY
Masters Student who has demonstrated a history of working as Analyst with advanced proficiency in Excel, Macro, Python with strong statistical background and knowledge of using SAS, SQL database and Tableau. Specializes in forecasting with in-depth knowledge of using Machine Learning Algorithms
CERTIFICATIONS AND TECHNICAL SKILLS
CERTIFICATIONS: Base Programmer for SAS 9 certification, Lean Six Sigma Green Belt, MySQL for Data Analytics and Business Intelligence, Tableau 2018: Hands-on Tableau Training for Data Science
LANGUAGES: SAS, VBA Excel, SQL, C, Python
APPLICATIONS: MS Office, Excel, Access
TOOLS: Tableau, @RISK, Palisade Decision Tools
STATISTICAL MODELLING: Exploratory Data Analysis, Time Series Analysis, ANOVA, Hypothesis Testing, Regression, Clustering, Classification, ARIMA, Neural Networks, Predictive Modelling, Cross Validation
LEAN / SIX SIGMA TOOLS: DMAIC, Value stream mapping, 5S, Root cause, PFMEA, 5 Why, KPI’s
EXPERIENCE
Graduate Teaching Assistant
UNC Charlotte, Charlotte, NC, Jan 2018-May2018
Helping students with ARENA software
Assisting the Professor in various tasks like Grading, Mentoring and Supervision
Supply Chain and Logistics Intern
Icomm, India, May2017-July2017
Increased efficiency, productivity of warehouse internal logistic and material flow operations by 30% (using Lean, DMAIC)
Eliminated obsolete material which had a financial impact on inventory holding cost and reduced excess storage
Programmer Analyst Trainee
Cognizant, India, August2016-December2016
Managed data storage through MySQL.
Bug fixes, performance improvements and further code enhancements.
Data Analyst
Srivari Construction, India, August 2015-May2016
Analyzing the cost and order quantity analysis for the raw materials to reduce inventory cost for the new projects
Successfully performed contract negotiations and analyzed supplier’s material quality
Demand planning and sales forecasting
PROJECTS
BigDEAL Forecasting Competition 2018 organized by Dr. Tao Hong
Secured 12th rank in the Qualifying match and 11th rank in the final match among 142 data scientists from over 20 countries. The competition was divided into two parts: Qualifying match consisted of hourly load forecasting for over one year and Final match where the task was to predict the probability of each hour being the peak hour of the day.
Software Used: SAS, Excel
Capstone Project Forecasting Competition - Daily Load Forecasting under Dr. Tao Hong
Secured 2nd rank and successfully improved the error accuracy of forecast from 7% to 3.12%
The project consisted of 2 phases: a qualifying phase where the model is built using Multiple Linear Regression in SAS Enterprise Guide and the final phase where the model is improved using the Gradient Boosting Algorithm in Python. Used Tableau for data visualization and creating Dashboards.
Forecasting Projects
Implemented Short term and Long term forecast models using Regression, Artificial Neural Networks, Clustering, Gradient boosting techniques.
Data cleansing and manipulation on raw temperature and load data using Excel, SAS Enterprise Guide
Experimented with ARIMA and time series forecasting models in Python to forecast daily demand
Performed probabilistic load forecasting by generating different temperature scenarios using Excel and SAS
Reproduced “Ensemble Learning Approach for Probabilistic Forecasting of Solar Power Generation”- Azhar Ahmed Mohammed and Zeyar Aung, with GEFCOM-2014 Solar dataset using Machine learning models in Python
Optimization Projects
Evaluated Linear Programming, Integer Programming methods using Excel Solver
Determined the Optimized route which meets all the constraints using shortest path algorithm in MATLAB for a small milk processing company
Predictive, Prescriptive and Descriptive Analysis using SAS E-miner
Performed Exploratory Data Analysis and Multiple Linear Regression on “Votes” data set using Base SAS
Using SAS E-miner tool, we performed predictive, prescriptive and descriptive analytics (EDA, logistic regression, clustering, association rule mining, decision tree modeling) on various standard datasets to learn the behavior of various datasets.
Restaurant/Café Reviews
The scope of project is to create a user interface application that allows users to search for a restaurant/cafe/pub in Charlotte, look for reviews and other related information and add reviews/ratings. This Application would also allow business owners to list their business and provide more details on their services and facilities
Technologies used: PHP, MySQL
Analysis of Employees database using MySQL and Tableau
Developed various complex queries using MySQL to analyze the Employees database from GitHub
The analysis helped us to understand relational databases and present the same using Tableau.
Designed of Experimentation for evaluating factors effecting the vacuum cleaners
Designed experiments using appropriate response variables, factors and levels, performed ANOVA analysis, Test for Independence, Barlett, Normality, SNK and Scheffe’s Test using Base SAS and Minitab
Process Analysis and Quality Control at Habesha Steel Mills
The manufacturing process for steel rods is audited for meeting and exceeding customer expectations with a process that is on target with the minimum variation possible
Tensile strength and yield strength are the two quality characteristics which constitute the continuous improvement of this project.
Tugger Route Analysis of Daimler’s Mt. Holly Manufacturing Plant
This project is to assess internal logistics and to optimize the material handling process on a systems analysis of Tugger routes in the Manufacturing Plant using Lean and Six Sigma methods
It improved 10% of Process Sigma and reduced cost by 2%
EDUCATION
Master of Science in Engineering Management – GPA: 3.71/4 December 2018
University of North Carolina at Charlotte, NC.
Undergraduate: Bachelor of Technology – GPA: 3.5/4 May 2016
Amrita School of Engineering, India.
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