As a Data Analyst, I utilized SQL to extract data from blockchain transactions and quadratic funding rounds. I conducted a thorough analysis of application rates and approval rates. Based on my findings, I prepared comprehensive charts to visually represent the observations

• Wrote python scripts for Excel data cleaning, cutting down 30+ hours of manual work each quarter and regularly analyzed office hardware specs via NLP for timely upgrades.• Administered Active Directory, maintaining security and permissions, while managing software updates for the department through Kace, ensuring optimal system performance.

• Developed a logistic regression model to predict customer churn in banking. • Evaluated model performance and feature relevance using k-fold cross-validation and conducted in-depth EDA to understand feature distributions. • Insights derived from the model informed client strategies, contributing to a 33% reduction in churn.• Engineered an automated boat detection system leveraging Mask R-CNN for segmentation and Optical Flow in OpenCV for image mask change detection.• Enhanced image quality using advanced dehazing, utilized GeoTIFF for accurate geo-location, and deployed YOLO for swift, precise object detection. Automated the workflow using AWS Lambda, SageMaker, and CloudWatch, reducing manual workload by 35 hours weekly.• Led the efforts to categorize customers of a restaurant chain with over 350 locations by safety perceptions and risk profiles using K-means clustering and RFM analysis. • Integrated NLP for sentiment analysis of feedback on safety during lockdowns. Utilized Tableau for visual analytics, aligning sentiment with demographics to devise precise marketing strategies, resulting in a better targeted marketing strategy.• Crafted an employee search tool with an R Shiny interface, utilizing R for data handling and text extraction from resumes. Applied text search and NLP to match and tag employees with specific skills. • Rolled out as an internal project for an organization with over 700 staff, enhancing the efficiency of talent identification.• Led a machine learning project to enhance medical record management for a provider with 2+ million records. Established an ETL pipeline via AWS Glue for efficient data handling and leveraged AWS Comprehend for NER, boosting record query speed and case segmentation accuracy.• Recognized with two Applause Awards for exceptional client service and timely delivery of projects and a Spot Award for implementing innovative solutions.

Created and implemented an ETL pipeline in SQL Server Management Studio for cleaning, structuring, and consolidating three Azure SQL databases into one. Also wrote triggers in place and stored procedures to identify and resolve errors and inconsistencies in tables while transferring.