Abhijith Dameruppala, M.S.

Data Scientist with expertise in Python, SQL, Machine Learning, and a proven track record in data-driven insights and solutions.

About

I am a versatile Data Scientist with a strong background in data analytics, machine learning, and backend development. With a Master’s degree in Data Science from Indiana University and a Bachelor’s in Electrical and Electronics Engineering, I’ve developed expertise in Python, R, SQL, and various database systems. My professional experience includes working on data-driven insights, predictive modeling, and system administration, where I’ve contributed to projects like content recommendation engines, A/B testing, and image classification using transfer learning. I’m also skilled in web development and backend technologies like .NET. I thrive in collaborative environments, leveraging data to solve complex problems and enhance business performance.

Education

Indiana University Bloomington

Masters, Data Science / May, 2024

Bloomington, Indiana, United States of America

Experience

Hoosier Community Network

Senior Data Science Consultant / July, 2024 — Present

● Developed scalable, cloud-based solutions using Machine Learning Algorithms, Agile methodologies, modern development and data science tools such as Python, SQL, R, and React.js ● Cleaned, modelled, and analyzed large datasets using SQL, NoSQL databases, and Python to create interactive data visualizations using tools like Tableau and D3.js to present complex data insights, enhancing data driven decision making accuracy by 15%. ● Operated CRM platforms and integrated Salesforce with data analysis workflows to streamline and automate data entry and reporting, improving client satisfaction and operational efficiency by 20%.

Accenture - Data Analytics and Visualization Job Simulation

Data Analyst / May, 2024 — June, 2024

● Completed a simulation focused on advising a hypothetical social media client as a Data Analyst at Accenture. ● Cleaned, modeled, and analyzed 7 datasets to uncover insights into content trends to inform strategic decisions. ● Prepared a PowerPoint deck and video presentation to communicate key insights for the client and internal stakeholders.

IU Fleet Services

Data Analyst / December, 2022 — May, 2024

● Leveraged Python, and SQL to analyze TransLoc ridership data, pinpointing peak usage times and areas and implemented A/B Tested Route Adjustments that cut average user wait times by 10 minutes. ● Generated insights using Tableau on ridership data, informing stakeholders’ decisions on fleet size. ● Conducted predictive analysis to forecast future ridership patterns and demand spikes, enabling adjustments to fleet management and resource allocation ahead of time.

Indiana University, Bloomington, IN

Graduate Teaching Assistant (Aug 2022 – Dec 2022) / August, 2022 — December, 2022

● Introduced students to R and Python for statistical modeling, enabling them to make data-backed decisions. ● Enhanced students' proficiency by 30% through instruction in regression analysis, and interpretation techniques. ● Integrated R for advanced statistical tests, increasing research rigor and improving data insight accuracy by 12%. ● Coded an automated feedback system using Python boosting efficiency of grading and feedback loop by 50%.

Wrytin, India

Data Scientist (May 2021 - June 2022) / May, 2021 — June, 2021

● Built a Content Performance Prediction Model in Python using XGBoost for multiclass classification, and sentiment analysis for classifying the emotional tone using 100K+ content records. ● Designed machine learning models, including Random Forest, SVM, and KNN, to recommend content trends for content creators, resulting in a 25% increase in content relevance and user engagement. ● Organized data-driven workshops with content teams using Power BI to visualize and communicate SEO strategies. ● Implemented Natural Language Processing (NLP) techniques for sentiment analysis on user feedback, providing actionable insights to the content team and improving user satisfaction by 15%.

Links & Social Media

GitHub

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