Data analysis, Python, SQL, Tableau, Statistical analysis
Resume:
BRUNDA CHOUTHOY
DATA AND ANALYTICS
CONTACT
***********@*****.***
Dublin, CA (SF Bay area)
linkedin.com/in/brundachouthoy
github.com/bruchouthoy
PROFILE
Aspiring data analytics professional with
a strong background in big data,
statistics and database processing.
Over 3 years of industry experience in
consumer oriented e-commerce product
environment with good analytical skills
and strong problem solving capability.
EDUCATION
2016 - 2017
DEPAUL UNIVERSITY [CHICAGO, IL]
Masters in Predictive Analytics [3.9/4]
2006 - 2010
VTU PESIT [BANGALORE, INDIA]
Bachelors in Information Science[3.8/4]
TECHNICAL SKILLS
§ Python, SQL, R, Linux OS
§ Statistical analysis – Regression
models, Hypothesis testing
§ Data Visualization – Tableau
§ Machine Learning
§ ETL and Data pipelines
§ Software Engineering
§ Distributed Systems – Hadoop,
MapReduce, Apache Hive, HDFS
MANAGEMENT SKILLS
§ Agile Development
§ Project and Team Management
§ Git, SVN, Excel, Powerpoint
EXPERIENCE
2011 - 2014
Senior Software Engineer Opentext
§ Responsible for feature development, production engineering support and technical consultancy for various legacy products owned by the team.
§ Worked in a challenging environment to analyze and provide engineering solutions to clients. Actively collaborated with cross functional teams for product deployments and migration.
§ Interfaced with customers to receive valuable product feedback.
§ Worked primarily on Web applications, Microsoft SQL Server, Oracle 11G, Unix/Linux Servers, Java and J2EE technologies. 2010 – 2011
Software Engineer Trainee Infosys Limited
§ Underwent training in the core concepts of databases, SQL and object oriented programming languages such as Java. PROJECTS
§ Predictive analysis on Readmission of Diabetes patients: The goal was to explore various classification models such as Decision trees, Naïve Bayes, SVM and Random forest to conduct a performance assessment using KPI’s. Results from this data analysis concluded in the direction of successfully predicting whether a patient will be readmitted with 30 days of discharge or not. Used Python.
§ Twitter data analysis: A large scale data analytics project involving Data extraction, Transformation and Loading (ETL) from a twitter data file to SQLite database using Python libraries. Worked on data transformation, summarization, querying and analysis to generate and provide insights.
§ Data Exploration and analysis of Kobe Bryant’s career data using Tableau: Worked on data exploration and visualizations for the
“Kobe Bryant’s shot selection” data obtained from Kaggle. Identified compelling ways to highlight Kobe’s career in the NBA from a purely analytical viewpoint.
§ Performance Analysis using big data utilities: Evaluated and compared the performance of execution costs for large-scale data using different AWS Hadoop cluster configurations using Hadoop streaming, Apache Hive and Pig.
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