Naga Manikanta Gudapati

+1-623-***-**** • aduz1a@r.postjobfree.com

EDUCATION

Master Of Science, information technology December,2022 Arizona State University, Tempe, AZ CGPA: 3.94 /4

Bachelor in Electronics and Telecommunication Engineering May,2019 Sardar Vallabhbhai National Institute of Technology. CGPA: 3.5/5.0 TECHNICAL SKILLS

Core Competencies: Object Oriented Design Agile Methodologies Data Structures and Algorithms Web development Scrum Artificial Intelligence Amazon Web Services Software Development Life Cycle Unit Testing

• Programming Languages: Python, C, Java. • Web Technologies and databases: HTML, CSS, JavaScript, React.js, MySQL, AWS Cloud Architecture, PostgreSQL. • Proficient tools: Power BI, ETL, Microsoft Office Suite, Oracle, GitHub, Selenium, Tableau, Visual Studio, Sales Force Administrator, Postman API Testing, Matplotlib, seaborn, MS Excel VBA, Microsoft SSIS, Data warehouse, Data Mining. Python Libraries: pandas, NumPy, matplotlib, seaborn, sklearn, prophet, stats models.

PROFESSIONAL EXPERIENCE

Arizona State University, AZ 08/2021 – 12/2022

Student Success Analyst

• Data collection and preprocessing the data collected from students reviews to the professors and graders increased productivity by 60% with a team of 2.

• Designed the sentimental analysis Models for review in python and visualizing the result Dashboards using Tableau.

• Conducting the meeting with managers and professors for weekly and monthly reviews.

• Teaching Assistant in Project Management for Engineering Students and Database Migration Expert.

• Improved inventory management by documenting sales, purchases, and supplier history in ERP saving 25 hours of manual work per week.

Affine Analytics- Hyderabad, India: Data Analyst 09/2019-10/2020

• Prepared training data by removing outliers and performing statistical analysis like correlation index, Enova, t-test to extract relevant features. Data analysis and Data Visualization on ticket data by using pandas, matplotlib and seaborn libraries.

• Predicted the type and count of issues by using regression techniques like Decision Tree Regression & Identifying the root-cause of an issue with the help of LSTM sequence generation techniques.

• Auto-Trigger the existing bots to resolve the root cause to provide uninterrupted services. Impact: Achieved an accuracy of around 70% in predicting the data and helped in providing efficient services and support for the client. RELEVANT PROJECTS

Speech Recognition Project Using NLP December 2021

• Designed a model which can identify and verify the efficiency of Speech to text Google API ‘s for different dialects.

• Conceptualized the Recognize google and SSL libraries in Python to take the input and how precisely the API’s Convert the speech to Text and the calculated values are transferred into the xl file and its around 92%.

• Tableau Dashboards are used to visualize how average accuracy of API’s varies with different demographics, age, gender. Project management system, class project spring 2021

• Developed a Project management system taking small software organization as a reference from scratch using ORM (Object Role Modelling) diagram till implementation in MSSQL and Couch Base.

• With this data model, companies can deploy their project details and other confidential data and managerial members can use it to identify points of failure and increase efficiency and productivity by 40% using NOSQL and MySQL in Cassandra database. Prediction of Fare of Airlines Tickets using Machine Learning Algorithms in Python January 2019

• Data Preprocessing; Feature, and Label Encodings; handing missing data, and outliers; Best Feature Selection; Built various ML models: Random Forest, Linear Regression, KNN, Decision Tree; Hyper Parameter Tuning for the model with high accuracy, and cross-validate the model

New York city Airbnb Analysis & Recommendation Summer 2022

• Translated end-user needs into data analysis requirements, built a model, and recommended a marketing strategy.

• Performed feature engineering, data transformation, model interpretation, and evaluation, for descriptive and predictive analytics.

• Compared the efficiency of models like linear regression, random forest, and gradient boosting by training using the Airbnb dataset.

• Predicted data with an accuracy of roughly 80% and assisted in finding profitable and popular places for building up Airbnb hotels and residences in the world's largest metropolis, New York. Interactive Report design to analyze and visualize data for Adventure Works Cycles in Power BI May 2021

• Connected & transformed the raw data; Created table relationships & data models; Analyzed data with new calculated columns & DAX measures; Visualized data with Power BI reports.

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