Resume
Skills
Python (Pandas, Vader, Numpy, Scikit-Learn, Matplotlib, Seaborn)
SQL
AWS S3
Microsoft Excel (VLOOKUP, PIVOT, CONCAT, TRIM, FILTER)
Tableau, Microsoft Power BI
Hadoop
Education
Master's in Data Science
DePaul University
June 2022 - June 2024
Chicago, IL
Relevant Coursework: Data Analysis and Regression, Python Programming, Database Processing for Large Scale Analytics, Data Visualization, Programming Machine Learning Applications, Mining Big Data, Intelligent Information Retrieval.
Bachelor of Engineering
SJB Institute of Technology
August 2016 - August 2020
Bangalore, India
Relevant Coursework - Operating systems, Network Analysis, Object oriented programming with C++, Programming in C and Data Structures, Wireless & Mobile Communication.
Experience
Data Analyst (Non-Profit)
Yiddishland Califronia
Nov 2024 - Present
Chicago, IL
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Utilized Pandas and NumPy to clean and analyze over 45K emails data, selecting key metrics for performance evaluation across multiple platforms.
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Implemented sci-kit-learn models (Linear Regression, Time Series Forecasting), achieving 85% accuracy in predicting future engagement and content success rates. Analyzed social media KPIs using Meta Business Suite API for insights on engagement and growth.
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Created data visualizations using Matplotlib and Seaborn, analyzing trends in 100+ posts, reels, and stories, identifying top-performing content types.
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Data Analyst
Vaeso
Sept 2020 - May 2022
Chicago, IL
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Analyzed large-scale operational datasets using SQL and Python, optimizing inventory management and improving operational efficiency by 30% through trend identification.
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Developed and optimized ETL pipelines leveraging AWS services like Lambda and Athena, reducing processing time by 20% and streamlining data ingestion, transformation, and integration.
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Designed and implemented interactive dashboards using Tableau, reducing manual reporting time by 45% and enhancing real-time data visibility for stakeholders.
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Applied machine learning techniques for anomaly detection and predictive modeling, increasing forecasting accuracy and enabling proactive operational insights.
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Ensured data quality and accessibility by implementing data-wrangling techniques, supporting informed decision-making processes and improving data reliability.