Abhishek Anumalla, an accomplished Data Analytics Engineer pursuing a Master's degree with a perfect GPA at George Mason University, exhibits a versatile skill set spanning programming languages, statistical analysis, and project management. With a robust foundation in Computer Science and Engineering from JNTUH-India, Abhishek has honed expertise in diverse areas including Web Development, Machine Learning, and Data Mining. Abhishek's professional journey includes a tenure as a Software Development Engineer at Mindtree L&T, where his pivotal contributions underscored the technical prowess and leadership qualities he possesses. Noteworthy projects at George Mason University demonstrate Abhishek's proficiency in leveraging advanced analytics techniques to solve real-world problems, further solidifying their reputation as a dynamic and innovative professional.
May 2024 - Aug 2024
Led the development of a Smart Forms landing page for organizational vendors, streamlining navigation and facilitating various agreement requests (NDA, MSA, SOW). Effectively managed API integration with Coupa, Conga, and NetSuite, significantly reducing manual work by approximately 80 hours. Designed PowerBI reports and wireframes for the smart form page, conducted thorough validation and sanity checks on 15 Power BI reports, ensuring data accuracy through cross-referencing with Cardinal data. Directed daily standups with a 7-member offshore team, managed project timelines, and collaborated closely with the Chief Information Officer. This initiative is projected to enhance efficiency by 200% by eliminating the need for additional cloud tools.
Jan 2021 - Dec 2022
Got trained extensively in Web Application Development using Java, .NET and SQL in the organization and worked on web applications handling banking and financial data which were built on all kinds of .NET frameworks- .NET, .NET Core, MVC, Web Forms. Also, worked on the front end using Infragistics controls, Bootstrap, jQuery, Ajax, JavaScript, HTML, CSS.
May 2023
To infer links between variables and discover correlations, the Diabetes dataset is statistically analyzed and shown. The best model is then selected after the dataset has been trained using several machine learning algorithms. To determine whether a patient has diabetes or not, an interactive interface was created using the SHINY application of R. R, Statistics, Visualizations, Random Forest Classification, Logistic Regression, and K-Nearest Neighbors were part of the software stack.
December 2023
The Cervical cancer dataset is statistically examined and displayed in order to deduce relationships between variables and find correlations. After the dataset has been trained using a variety of machine learning algorithms, the best model is chosen. Using the Python DASH framework, a web application was designed where an interactive interface was developed to ascertain whether a patient has cervical cancer or not. The software stack included Python, R, Statistics, Visualizations, Random Forest Classification, Gradient Boosting Classification, Support Vector Machine, Logistic Regression, and K-Nearest Neighbors.
2023-2024
George Mason University, Virginia
Data Mining (WEKA Machine Learning algorithms, Entity Relationship Diagram, SQL), Decision Analysis (R and Python Programming for Analytics and Visualizations), Applied Statistics & Visualization of Analytics (R programming, Web development in R using Shiny, RMarkdown), Analytics and Modeling (Operations Research Techniques, Optimization, Network modeling, Monte Carlo Simulation, Decision Trees), Metadata Analytics for Big Data (Web development, Putty, Remote Desktop Deployments, Python Dash app development, Machine Learning Modeling, FileZilla), Big Data Essentials (Databricks, R, Python, Tableau, SQL, NoSQL, HDFS, HIVE, PIG, Spark MLlib)
2016-2020
JNTU, Hyderabad, India
Database Management Systems (ER Modeling and SQL), Data Structures using C programming, Design and Analysis of Algorithms (Floyd’s, Knapsack, Prim’s and Kruskal’s Algorithms, Traveling Salesman Problem), Computer Networks (Network Layers, Client-Server transfer, Network Communication Protocols), OOPS through C++, Android Development, JAVA Programming, Operating Systems, Web Development and Perl scripting.
2014-2016
School of Secondary and Intermediate board
Mathematical Induction, Matrices, Addition of Vectors, Product of Vectors, Trigonometric Ratios up to Transformations, Trigonometric Equations, Inverse Trigonometric Functions, Limits and Continuity, Three-Dimensional Coordinates, Direction Cosines and Direction Ratios, Differentiation , Applications of Derivatives Introduction, Hyperbolic Functions
Address
George Mason University, Fairfax, Virginia, U.S.A
Phone
+1 814-308-4053
aanumall@gmu.edu