Ragahava Prasad Sridar is a business analytics professional with a Masters in Business Analytics from The University of Texas at Dallas. He has over 3 years of experience in data analysis, machine learning, and database management. His technical skills include Python, R, SQL, Tableau, and Hadoop. He is pursuing a career in data science and analytics and is looking for internship or full-time opportunities.

1. RAGHAVA PRASAD SRIDAR
+1(469)-439-9290
rsitprasad001@gmail.com
https://www.linkedin.com/in/raghava-prasad-s/
EDUCATION
The University of Texas at Dallas​, Dec 2021
Masters in Business Analytics 3.78 CGPA
SCSVMV University​, Jun 2017
BE in Computer Science and Engineering 3.1 CGPA
CERTIFICATIONS & TECHNICAL SKILLS
Databases​ - SQL, Cassandra QL, MongoDB, Neo4j, Cypher, PostgreSQL, MySQL, Oracle DB, Amazon Redshift
Programming languages​ - R, Python, Stata, C++, Java
Visualization / Intelligence tools​ - Tableau, Rapid Miner
ETL tool​ - Pentaho
Big Data Suite​ - Hadoop Map Reduce, Apache Spark , Apache Splunk, Gephi, SparkSQL, Redis
Other tools​ - Microsoft SQL Server, MS Excel, R Studio, Microsoft Visual Studio Code, Tableau Desktop,
Microsoft Office, Microsoft Azure, Amazon SageMaker, Amazon GluonCV
Certifications ​- Big Data Specialization, Data Visualization with Python, Neural Networks and Deep Learning, EMC2 Cloud Architecture
COURSEWORK
Applied Econometrics and Time Series Analysis​ - STATA, Economic theory, Regression Analysis, Empirically
estimate interpret commonly used economic techniques to analyze cross-sectional, time series and panel data sets
Statistics and Business Analytics​ - Statistical and Probabilistic Methods, Decision Analysis, Confidence Intervals and
Hypothesis Testing
Business Analytics with R​ - R programming, Statistical Analysis using R Libraries, Machine Learning using R
BUSINESS EXPERIENCE
Programmer Analyst, Cognizant Technology Solutions​ ​Nov 2017- Sep2019
● Worked for the Benchmarking and Project Tracking Team. Core responsibilities included analyzing and reporting pitfalls that diminished
the quality of an application measured using several parameters.
● Improved the performance score of an Internal Application by 6% through analyzing and Reporting the Root Cause for performance
deficit.
● Performed Risk Prediction for a Critical Application with Microsoft Azure Machine learning Tool and R Language that helped in preventing
the potential projects from falling under Risk category beforehand.
● Designed and Developed a database fully from scratch, and performed other data transformation activities for a wide array of US clients
Solutions Engineer Intern, Nokia Solutions and Networks​ ​Aug 2017- Nov 2017
● Worked for the Innovation Management team to study potential applications of augmented reality with Microsoft Holo-Lens that can be
applied within the industry for training entry level assemblers.
● Developed a web application working for the Internal application development team using C#.Net and SQL.
ACADEMIC PROJECTS
● Time Series Analysis​ on Traffic Deaths across the states of US, researching on how drinking laws affect traffic deaths using ​STATA​.
● Face Recognition using Python​, ​OpenCV . Detected faces and facial properties , trained the model and built a face identification
system that identifies faces.
● Object Detection System using Amazon SageMake​r - Built an end to end ML model using Images of bees as training data, with
customized hyper parameters to achieve accurate Object detection.
● Catch the Pink Flamingo​ - An Imaginary Game by Euglence Inc, as a part of Big Data Specialization - Performed
Analysis using Apache Splunk, and built ​Classifiers ​using ​KNIME ​and queried the data extensively using ​Cypher
using Neo4j Graph Database.
● Twitter Sentiment Analysis (​R, Weka, CARET​) Performed Sentiment Analysis of Twitter feeds to gauge the reaction of fans in cricket
matches in Indian Premier League (a leading cricket tournament).
ADDITIONAL INFORMATION
Organizations - Member, Data Science Club (Jan 2020- Present) Author, Medium.com (Apr 2020- present)
Eligibility - ​Eligible to work in the U.S for internships and for full-time employment for up to 36 months (STEM Only)