Experienced Data Analys with 5+ years in Aviation, Banking, Retail and Healthcare industries.
A seasoned Data Analyst with over five years of experience translating complex, high-volume datasets into strategic assets across diverse industries including Aviation, Finance, Banking, Supply Chain, Retail, Warehouse, and Healthcare. My expertise encompasses the full data lifecycle—from advanced data mapping, cleansing, and validation using SQL and Python, to the development of compelling, high-impact visualizations in Tableau and Power BI that drive executive decision-making.
I am adept at bridging technical and business domains, evidenced by significant contributions to critical documentation (BRD, FRD, SRS) and a proven ability to navigate the full SDLC within Agile and Scrum frameworks, consistently delivering solutions that enhance operational efficiency and uncover pivotal business insights
As an aspiring innovator, I am committed to leveraging my skills to develop intelligent systems that have a positive impact on people's lives. If you share the same enthusiasm for machine learning and are eager to embark on this exhilarating journey with me, I invite you to connect with me. Together, let's explore the possibilities and create something extraordinary! Looking forward to connecting with like-minded individuals and achieving great things together!
Led analytics, automation, and regulatory compliance for 100+ weekly international cargo flights with a focus on Dangerous Goods and high-value shipments.
Spearheaded Python-based ETL automation and route optimization, increasing data accuracy by 15% and processing speed by 20%.
Built Tableau and Power BI dashboards that enhanced throughput by 10% and provided operational insights across 5+ departments.
Maintained 100% DG compliance and zero documentation errors on shipments over $1M using SQL verification scripts ensuring seamless audits.
Analyzed cargo KPIs using complex SQL queries in Snowflake and Teradata data warehouses to identify performance gaps and enhance operational throughput.
Developed predictive models in Python (Scikit-learn) to forecast space utilization, achieving 7% optimization in load factor.
Automated executive-level compliance and performance reports, streamlining reporting cycles by 30% and aligning with data governance standards.
Collaborated cross-functionally to translate complex data into clear, actionable insights for diverse stakeholders.
Delivered advanced analytics and reporting to support risk modeling, collections strategy, and customer retention.
Built predictive models in Python with 95% accuracy, cutting charge-offs by 12% and increasing retention by 5%.
Forecasted recovery performance using AWS and SQL, boosting profitability by $100K.
Implemented A/B testing and UAT analytics pipelines, enhancing campaign precision by 20% and providing key insights for executive teams.
Created data-driven dashboards in Power BI and Tableau, improving reporting efficiency by 30%.
Analyzed customer behavior patterns, improving risk factor identification by 15%.
Analyzed retail data across 31 stores and a distribution center to enhance marketing, inventory, and operations.
Optimized ETL and data warehousing processes using SQL, Redshift, and Python, improving data accessibility and schema design. Achieved 4% reduction in data retrieval time.
Drove $1.2M revenue growth through sales trend analysis and dashboard implementation.
Created Tableau and Power BI reports to visualize product performance and inventory cycles. These insights resulted in 5% inventory optimization.
Boosted customer loyalty by 30% and expanded the customer base by 20% by introducing "Subscription Purchases" and "Recipe Integration" strategies through SAP CRM segmentation and targeted marketing.
Supported data ETL, reporting, and documentation initiatives across multiple healthcare data systems.
Performed ETL operations on 7M+ records from SQL Server, Various filetypes into Redshift using SQL and Python.
Created SQL-based reports and documentation for compliance and internal performance monitoring, improving overall performance oversight.
Improved data quality by 10% through validation and implementation of best practices across cross-functional teams.
A rigorous graduate program focused on advanced concepts in machine learning, deep learning, natural language processing, and data-driven decision-making. The curriculum emphasizes practical application through hands-on projects, research, and real-world problem-solving across diverse domains.
Comprehensive undergraduate program covering core areas such as algorithms, data structures, software engineering, databases, operating systems, and computer networks. Emphasized hands-on experience through coding projects, collaborative development, and practical application of computational problem-solving.
This project aims to develop a Python script using Selenium to automate scraping YouTube video details for topic-specific datasets. Extracting key information like titles, channels, views, and thumbnails, the project aims to provide users with a streamlined tool for efficient data collection and analysis.
