Spandana Chepuri

Academic Background: I graduated with a Master's degree in Data Sciences and Applications from The State University of New York at Buffalo, where I gained comprehensive knowledge in various subjects, including Programming Database Fundamentals, Database Management Systems, Numerical Analysis, Probability and Data Analysis, Statistical Data Mining, Machine Learning, and Cybersecurity Privacy and Ethics. These courses have equipped me with the necessary skills to excel in the field of data science. My Bachelor's in Computer Science and Engineering from JNTU Hyderabad (TKR College) provided a strong foundation in technology, where I honed my problem-solving skills through programming in C and C++, gained a deep understanding of computer systems through Computer Organization and Architecture, and developed practical expertise in building and managing web applications. Additionally, I acquired essential knowledge in networking, advanced my proficiency in Java and Data Structures, and explored the innovative world of IoT, all of which fueled my passion for technology and prepared me for advanced studies in data science.

Practical Experience:Building upon my strong academic foundation, I have engaged in hands-on projects that have expanded my expertise in data science and engineering. One of my key projects was the Citywise 311 Case Analysis, where I led a team in implementing Naive Bayes classification to predict ticket volumes and resolution times using data from cities like Boston, New York, and Chicago. Additionally, I spearheaded the development of the TICKETO Database, designing a robust architecture to manage event data from multiple sources, including payments and advertising campaigns, which significantly improved efficiency and strategic insights. Through my internships at CISCO Networking Academy and Manac Infotech, I gained valuable experience in cloud migration, real-time data processing, and optimizing workflows using tools like Google BigQuery, AWS Lambda, and Airflow.

Technical Skills: I have built a solid foundation in programming languages, including Python, Pyspark, SQL, R, C++, C, Java, HTML, and CSS. I am familiar with a range of libraries and databases, such as Redshift, Snowflake, SQL Server, BigQuery, Airflow, Hive, Pandas, NumPy, and Scikit-learn. Additionally, I have gained practical experience with cloud platforms like AWS and Google Cloud Platform (GCP), which has prepared me to effectively contribute to data-driven projects.

Professional Experience: My progression into the field of data science and engineering has been solidified through a series of technical internships, where I gained practical experience and advanced my proficiency in key industry tools and methodologies:

Virtual Intern at CISCO Networking Academy: During this internship, I contributed to the development of a financial data analysis pipeline, integrating Google BigQuery and Pub/Sub to handle 100GB of data daily. My work facilitated strategic insights for the company and improved decision-making efficiency by 30% through the creation of interactive, real-time dashboards in Data Studio, powered by optimized Dataproc and Airflow processes.
Intern at Manac Infotech: Here, I played a crucial role in transitioning SQL Server to AWS, significantly enhancing the scalability of a startup handling over 100k monthly transactions. I also configured and optimized AWS Glue ETL pipelines, reducing processing time by 40% for immediate inventory and customer insights, and deployed AWS Lambda to streamline data workflows.

Summary: As a passionate and driven data science enthusiast, I have developed a solid foundation through rigorous academic training and hands-on internships. My expertise spans programming, data analysis, machine learning, and cloud computing, which I have applied in various projects and real-world scenarios. I am eager to bring my skills to a full-time role where I can contribute to impactful data-driven solutions. If you are interested in learning more about my work or have opportunities that align with my skills, please feel free to check out my Resume or send me an e-mail. I would be delighted to connect and discuss how I can contribute to your team!

~ Email | Resume | Github | LinkedIn ~

Dec '24	Completing my final semester of the Master's in Data Sciences and Applications at the University at Buffalo.
Aug '23	Began my graduate studies in Data Sciences and Applications at the University at Buffalo.
July '23	Graduated with a Bachelor of Technology in Computer Science and Engineering from JNTU Hyderabad (TKR College).
May '23	Earned a Gold medal for outstanding academic achievement during my Bachelor's in Computer Science and Engineering at JNTU Hyderabad (TKR College).
Dec '22	Completed a Virtual Internship at CISCO Networking Academy, where I contributed to the development of a financial data analysis pipeline.
May '22	Completed an internship at Manac Infotech, where I played a key role in transitioning SQL Server to AWS, enhancing scalability.
Aug '19	Began my Bachelor of Technology in Computer Science and Engineering at JNTU Hyderabad (TKR College).

State University of New York at Buffalo

Master of Professional Studies | Data Science Aug '23 - Dec '24
Coursework:
• CDA 502/MGS 613: Database Management Systems
• CDA 511: Introduction to Numerical Analysis
• EAS 503: Programming Database Fundamentals
• CSE 574: Machine Learning
• CDA 531/MTH 511: Probability and Data Analysis
• CDA 541/STA 545: Statistical Data Mining 1
• CDA 532/STA 546: Statistical Data Mining 2
• CDA 551/MGS 639: Cybersecurity Privacy and Ethics
• EAS 504: Applications of Data Science Industry Overview
• MGS 628: Data Visualization for Business

Jawaharlal Nehru Technological University Hyderabad (TKR College)

Bachelor of Technology | Computer Science and Engineering
Aug '19 - July '23
Coursework:
• Data Structures
• Design and Analysis of Algorithms
• Computer Networks
• Operating System
• Computer Architecture
• OOPS through Java
• Software Testing Methodologies
• Computer Oriented Statistical Methods

Virtual Intern | CISCO Networking Academy
Hyderabad, India
Dec '22 - June '23

Big Data-Driven Financial Insights: Enhancing Decision-Making with Real-Time Dashboards
• Engaged to development of a financial data analysis pipeline, integrating Google BigQuery and Pub/Sub to handle 100GB daily, facilitating strategic insights for a networking firm.
• Collaborated on crafting interactive, real-time financial dashboards in Data Studio, powered by optimized Dataproc and Airflow processes, driving a 30% boost in decision-making efficiency.

Intern | Manac Infotech
Hyderabad, TS, India
May '22 - Nov '22

Cloud Migration & Automation: Scaling Data Workflows with AWS Glue and Lambda
• Integrated SQL Server to AWS transition, boosting scalability for a startup with 100k+ monthly transactions.
• Configured in crafting AWS Glue ETL pipelines, slashing processing time by 40% for immediate inventory and customer insights.
• Deployed AWS Lambda automation to streamline data workflows, enhancing analytics efficiency.

Citywise 311 Case Analysis: Predicting Ticket Volumes and Resolution Times using Naive Bayes Classification

Technologies: Python, Naive Bayes, Pandas, NumPy, Jupyter Notebook | Oct. 2023 - Dec. 2023 [code][Database Schema]

• Leading a team of four, Implemented Naive Bayes classification on 311 case data from cities such as Boston, New York, and Chicago, predicting ticket volumes and average resolution times as part of academic coursework.
• Used historical case data to train the model and improve the accuracy of service demand forecasting.
• Developed visualizations to analyze ticket trends and provide actionable insights for city management.

TICKETO Database: Streamlining Event Data Management

SQL, AWS, Python, Pandas, Database Architecture, Data Management, Strategic Planning | Aug. 2023 - Dec. 2023 [code][Report][Dashboard]

• Led team in designing a robust TICKETO database architecture, enriching storage and strategic planning for processing of information from 10 distinct data origins, including payments, advertising campaigns, and consumer feedback.
• Executed enhancements with a group of four for increased efficiency and insights, involving strategic planning as part of academic studies.

Paper 1 Underwater Image Enhancement Using CNN	Journal ZKG International
Authors Ritika Nandagiri, Karthik Panuganti, Spandana Chepuri	Link Write_Up
Paper 2 Software Defect Estimation using Machine Learning Algorithms	Journal IJARST
Authors Dr.M.Dhasaratham, Spandana Chepuri	Link Write_Up

	Goldman Sachs - Software Engineering Virtual Experience Program (2023) Feb. 2023 [Certificate] • Completed the Software Engineering Virtual Experience Program at Goldman Sachs in 2023. The program focused on managing a leaked password database, which reinforced my skills in database security, encryption, and data management, directly complementing my data science and database coursework.
	Hackathon Organizer - Developers Go (2023) March. 2023 [Certificate] • Organized and led the "Developers Go" hackathon at my undergraduate college, sponsored by academic affairs. I mentored participants in data-driven project development, guiding them through the integration of tools such as Python and SQL for back-end data processing, as well as Tableau and Power BI for real-time data visualization. The hackathon focused on leveraging ETL pipelines for efficient data transformation and using machine learning algorithms for predictive analytics. My guidance ensured participants applied these technologies to solve real-world problems, enhancing their proficiency in data science workflows.
	International Workshop on AI/ML - Brainovision Solutions (2021) Sep. 2021 • Participated in a six-day international online workshop on AI/ML, organized by Brainovision Solutions in collaboration with my undergraduate college. The workshop provided hands-on experience with various machine learning algorithms, including supervised and unsupervised learning techniques. I gained practical exposure to neural networks and deep learning using frameworks such as TensorFlow and PyTorch. The workshop also emphasized the deployment of ML models in production environments, focusing on tools like Keras for model development and scikit-learn for data preprocessing and evaluation. This enhanced my understanding of AI/ML applications and strengthened my skills in building scalable and efficient machine learning systems.
	Alien Fest 2.0 - Workshop on Mobile App Development (2020) Oct. 2020 • Participated in the Alien Fest 2.0 tech fest held in Hyderabad in 2020, where I attended a workshop on mobile app development. The workshop focused on mobile application design, emphasizing front-end and back-end integration. I learned about using Android Studio for app development, managing databases with SQLite, and implementing scalable backend architectures through REST APIs. The session also covered data management strategies, with a focus on integrating cloud services like Firebase for real-time database handling. This experience enhanced my understanding of the interplay between mobile apps and database management, aligning with my academic studies in data-driven architecture and scalable solutions.

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