Venkata Sai Savant Mullapudi

Salt Lake City, UT *4101

+1-385-***-**** ad3ccg@r.postjobfree.com

linkedin.com/in/savantmullapudi

Education

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Master’s in Computer Science Aug 2023 – Present

University of Utah, Salt Lake City, UT

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Bachelor’s in Computer Science and Engineering Aug 2018 – Jul 2022 MVGR College of Engineering,Vizianagaram, India

Skills

• Programming Languages: Python, Java, C, SQL, HTML, CSS, Javascript, APEX

• Technologies: AWS, Salesforce, CCNA networking, Devops Experience

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Assistant System Engineer Jul 2022 - Jul 2023

Tata Consultancy Services (TCS) Bengaluru, India

Conducted an IoT-based project leveraging AWS Stream services for real-time data ingestion, processing, and analysis.

Developed custom data processing applications using AWS Lambda, Python, and other relevant technologies, enabling real-time analytics and visualization.

Ensured data security and compliance by implementing encryption mechanisms and access controls using AWS Key Management Service (KMS) in accordance with industry best practices.

Actively participated in knowledge sharing within the team, contributing to internal workshops on IoT, AWS Stream, and data engineering techniques.

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Data Science Intern Mar 2022 - Jun 2022

Pro Digital Worx Inc Bengaluru, India

Developed predictive models, employing machine learning algorithms, to address challenges such as customer segmentation and demand forecasting.

Cleaned, preprocessed, and transformed raw data into usable analysis formats using Python and relavent libraries

(pandas, NumPy, and matplotlib).

Conducted exploratory data analysis (EDA) on various datasets to uncover patterns, trends, and anomalies, providing valuable insights for optimizing strategies.

Conducted a comprehensive workshop on the fundamentals of DevOps in collaboration with my mentors during my internship. This initiative aimed to provide insights into essential DevOps principles and practices.

Demonstrated a dedicated focus on effectively implementing Docker images and files. Proficiently engaged in tasks involving Docker to streamline application deployment, enhance scalability, and optimize resource utilization. Projects

• Sport Result Prediction: Created an innovative Sport Result Prediction project that centers on employing machine learning methodologies, including Naive Bayes, Logistic Regression, and Support Vector Machine, to forecast outcomes of sporting events.

• Fast Food Billing: Designed and Implement a rapid-service food billing solution as a team. This project enables customers to place orders through an online platform, generating menus and bills seamlessly, and ensuring timely delivery of selected items.

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