I am currently pursuing MS in Information Technology Management and will graduate in May-2020.
I would like to do blend my knowledge and skills into the field of Data Science.
I am comfortable working in R, Python, Tableau, SQL among many languages and tools.
Gautham Sai M.R
(469)349-7229
gauthamsaimr@gmail.com
Master of Science in Information Technology Management • May 2020
Relevant Coursework:
Agile Project Management
Business Data Warehousing
Statistics and Data Analysis
System Analysis & Project Management
Business Analytics with R
Econometrics and Time series Analysis
Web Analytics
Bachelor of Engineering in Information Science and Engineering • May 2018
Relevant Coursework:
Data Structures and Algorithms
Data Warehousing and Data Mining
File Structures
Object Oriented Programming
Software Testing
Database Management System
Operating Systems
Computer Networks
Software Engineering
Graph Theory and Combinatorics
Discrete Mathematical Structures
Data Analyst Intern • Aug 2019 - Present
•Created a Ranking algorithm for different clients located in the United States based on revenue generated by transactions per device by client employees, thereby increasing the performance of client employees by 40%Data Analyst• May 2017 - May 2018
•Tracked and inspected key performance indicators like cost of tickets sold, sales by region, number of customers and provide recommendation based on findingsBusiness Intern • Dec 2014 - March 2015
•Redesigned marketing plan for data collection which resulted in reduction of 10 man-hours per week and improved data qualityProgramming Languages: Python, R, C, C++, Perl, JavaScript, SAS
Machine Learning: Decision Trees, Naive Bayes, Support Vector Machines, Unsupervised Learning
Analysis Tools: Tableau, Advanced MS Excel, SAP BW, Google Analytics, JIRA, SAP Crystal Report, PowerBI, SAP Business Object, Alteryx, Informatica
Databases: MySQL, SQL server, Oracle
Microsoft Excel: Pivot Table, Data Analysis, Regression, Anova, Data Manipulation, Descriptive Statistics, VLOOKUP, Dashboards
• Analysed the effect of crime rate demographics using multiple regression on guns data with 1500 rows
• Developed a regression model on the panel data using fixed effects and modelled for time fixed effects on time variable, tested for heteroscedasticity, endogeneity and interpreted its significance
We proposed a system that generates natural descriptions of provided images, which can be utilized by the visually impaired population to further their own agendas, and contribute more productively to the society. We establish an encoder-decoder paradigm, where a VGG-16 network, followed by a LSTM network is trained to produce a mapping from images to sentences. Built the protocol to communicate with the client and server, found a way to achieve the real-time visual feedback. Implemented the Neural Network architecture. Used NumPy, Python along with TensorFlow for the Implementation Convolution Neural network architecture. Achieved a BLUE score of 28.2.
Prediction View Code
• Predicted the stock price of Ford Motors in python using the dataset of past 5 years from Yahoo finance • Developed cross-validated prediction model using Support Vector Regression with 95% prediction accuracy
Prediction View CodePublished a research paper at 2018 International Conference on Advances in Computing, Communications and Informatics (ICACCI).
Proposed a system that generates natural descriptions of provided images, which can be utilized by the visually impaired population to further their own agendas, and contribute more productively to the society. We establish an encoder-decoder paradigm, where a VGG-16 network, followed by a LSTM network is trained to produce a mapping from images to sentences.
Built the protocol to communicate with the client and server, found a way to achieve the real-time visual feedback. Implemented the Neural Network architecture.
Used NumPy, Python along with TensorFlow for the Implementation Convolution Neural network architecture. Achieved a BLUE score of 28.2.
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