*+ years of experience in Data Analytics with outstanding preeminence in Data extraction, Data cleaning, Data Loading, Statistical Data Analysis, Exploratory Data Analysis, Data Wrangling, Predictive Modeling using R, Python, and Data visualization tools.

EDUCATION:

George Mason University; Fairfax, VA GPA:3.8

Master of Science in Information Technology, Jan 2019 - May 2020.

Jawaharlal Nehru Technological University, India GPA:3.6

Bachelor of Technology in Electronics and Communication Engineering, 2014 - 2018.

SKILLS:

Data Analytics Tools

Tableau, RStudio, Microsoft Power BI, SAP Crystal Reports, SAP Lumira, Google Analytics, Weka, AWS, SAS, Qlik

Databases

My SQL, SQL Server, MS Access, MySQL, Oracle, RDBMS

Big Data

Hadoop, Spark, MapReduce, Hive

Programming Languages

SQL, R, Python, HTML, CSS, Visual Studio 2010/12, C++, Java

Microsoft Tools

MS Office Suite (Word, Excel, PowerPoint), Adobe Acrobat Reader

Operating Systems

Windows 2000/NT/XP, Unix, Linux.

EXPERIENCE:

Verato Inc, Mc Lean, VA – Data Analyst Jun ’20 – Dec ’20

Performed Manipulation, cleaning & processing of data using MS Excel, MS Access, and SQL.

Dealt with cleaning and transforming massive data into useful and insightful to specific teams with help of R and Python.

Performed Data entry, data auditing, creating data reports (Power BI) & monitoring all the data for accuracy.

Carrying out specified data processing and statistical techniques with the help of Python and R.

Involved with all the phases of Software Development Life Cycle (SDLC) methodologies throughout the project life cycle.

Analyzed client data to understand historical performance relative to the potential performance of programs, identify performance gaps and highlight performance improvement opportunities, and created useful graphs and dashboards by using Tableau and Excel Pivot tables.

George Mason University, Fairfax, VA – Data Analyst Mar ’20 – May ’20

Developed an advanced Excel spreadsheet for Professors to capture data about students.

Identified relevant trends, do follow -up analysis on performances, prepared visualizations in form of charts, graphs, and tables to understand identify Key Performance Indicators (KPI’s).

Reported, researched, corrected, and tested defects in reports, stored procedures, and other database-related functions.

Worked with RDBMS concepts for creating database objects such as tables, functions, stored procedures, indexes, views.

Utilized spark, Matplotlib, Python, a broad variety of machine learning methods, and Natural Language Processing (NLP) including classifications, regressions, dimensionally reduction, Neural nets, and Dimensionality reduction.

TechQuin Solutions Pvt Ltd., Hyderabad, India – Data Analyst Jan ’18 – Dec ’20

Developed, kept up, and executed SQL contents/questions and approved culmination, trustworthiness, and precision of information.

Designed database schema using MySQL created tables to store data and performed data manipulation.

Collaborated with BI teams to create reporting data structures, ensure data warehouse and data mart designs efficiently support BI end-users.

Used Multiple Linear Regression, Decision Tree Regression, Support Vector Regression & ensemble learning like Bagging, Random Forests & Gradient Boosting Machine to train 70% of the model & the models were optimized using Grid Search & the predictions were made on the test set using each trained model.

Tackled highly imbalanced Fraud Dataset using under-sampling, over-sampling with SMOTE, and cost-sensitive algorithms with Python.

Communicated the results with the operations team for making the best decisions.

ACADEMIC PROJECTS:

House Price Predictions – Data Analytics Jan ’20 - May ’20

Preprocessed the data by implementing Data Cleaning Protocols.

Designed and tuned Machine Learning models to predict housing prices, built and tested with Python and R.

Generated visualizations to predict the sale price of a house based on Key performance indicators generated from the Random forest model.

Performed analysis on how the well the designed model fits the data using regressions algorithms – Lasso, Support Vector Machine, Decision Tree, Multivariate.

Tools used: Python, R, Tableau, Power BI

FAERS data – Machine Learning – Data Analytics Feb ’20 - May ’20

The paper aimed to perform the categorization and characterization of populations affected by drug reactions.

Created a distributable model that estimates drug reaction fatality based on patient characteristics using unsupervised machine learning.

Generated valuable visualizations with Python and Tableau.

Tools & Machine Models designed: Python, Tableau, XGBoost Classifier algorithm with Standard Scaler – Wrapper

Type II Diabetes from EHR – Data Analytics Aug ’19 - Dec ‘19

The paper categorizes people into Diabetic & Non-diabetic by modeling various Machine learning and Deep learning models in python.

Machine learning models like Decision tree and Deep learning models like Artificial Neural networks are trained, evaluated using the K-Fold Cross Validation method, and the corresponding results are compared to determine the competitive models.

Tools & Machine Models designed: Microsoft Power BI, SQL, R, Decision tree, Artificial Neural Network

Analysis on Global Terrorism Attack – Big Data – Data Analytics Mar ’19 - Jun ‘19

Generated various Big data Visualizations using Spark, Python, and R to analyze the top 10 attack prone areas.

Designed appropriate Partitioning/Bucketing schema to allow faster data access using HIVE.

Used Hadoop ecosystem for processing the data.

Tools used: Spark, Python, R, Hive, Hadoop, Google collab

CERTIFICATIONS:

Tableau Scientist & Analyst (Tableau)

Google Analytics for Beginners & Advanced (Google Academy)

Python for Data Science (IBM)

R Programming (Udemy)

SQL (Test Dome)

SRIJA UMMANENI

Data Analyst Data Scientist Business Analyst Data Engineer

Phone: +1-571-***-****

E-Mail: adjkxk@r.postjobfree.com

Location: Herndon VA, 20171

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