- Collaborated with stakeholders to gather and translate business requirements into scalable, efficient data solutions.- Designed robust data systems to support analytics, reporting, and operational workflows.- Developed and optimized ETL pipelines in Azure using Logic Apps, Databricks, and Blob Storage, ensuring seamless data processing and transformation.- Leveraged tools like Airflow and dbt to automate workflows and enhance data integration processes.- Implemented advanced data modeling techniques to improve data accessibility and usability for analytics and reporting teams.- Created and maintained comprehensive documentation of system designs, workflows, and technical implementations to ensure clarity and continuity.- Monitored, troubleshot, and resolved issues in production data pipelines, ensuring reliability and optimal system performance.

- Designed and developed a comprehensive system to analyze market survey data and identify fraudulent responses, ensuring the integrity and reliability of survey results.- Collaborated with stakeholders to understand requirements and build solutions tailored to detecting anomalies and inconsistencies in survey datasets.- Engineered and optimized data pipelines to preprocess and analyze large volumes of survey data efficiently.- Implemented advanced statistical and machine learning models to flag fraudulent entries, achieving significant improvements in data quality and decision-making.- Created detailed documentation to support system architecture, workflows, and technical implementations for ongoing enhancements.

• Spearheaded the integration of cutting-edge technology, including Large Language Models (LLMs) and Retrieve Augmented Generation (RAG), to streamline literature review processes, enhancing efficiency and accessibility for research scholars.• Implemented user-friendly interactive application, enabling scholars to engage in real-time dialogue and query-based interactions (prompting), fostering swiftly accessing the information.

• Achieved significant operational cost savings and maximized sales opportunities for Graybar by pioneering a predictive analytics solution to optimize new stock item request decisions.• Developed end-to-end predictive model solution leveraging classification models to rank new stock item requests. Integrated this model into an interactive dashboard (Streamlit) via a scikit-learn pipeline, enhancing decision-making with actionable insights.• Acted as a single point of contact with the client and professor, understanding business requirements, coordinating the team, and leading the project with effective communication and collaboration.• Engaged clients through compelling PowerPoint presentations that seamlessly blended in-depth analysis, insightful findings, and actionable recommendations, effectively communicating complex ideas.

Solutions and Analytics partner to eCommerce brands and digital marketing agencies. Acted as a primary point of contact where I delivered data-driven solutions for brands operating in Amazon Seller Central (SC), Vendor Central (VC), and Shopify in space of advertising (PPC + DSP), sales, customer, inventory, and Finance.• Developed SQL data modeling in Snowflake, Azure SQL Server, BigQuery, and dbt, optimizing queries for faster insights and efficient ETL processes using Python for ecommerce clients.• Leveraged Business Intelligence (Power BI) for automated intuitive interactive reports by writing complex DAX queries, resulting in elevated data quality and optimized decision-making processes.• Automated inventory restocking decisions with ensemble regression techniques on historical data, factoring in lead times and minimum weeks of coverage. Achieved a 15% reduction in stockouts and a 10% decrease in excess inventory costs.• Delivered comparative analytics to a brand and crafted data simulations facilitating a seamless transition from vendor central to seller central, resulting in increased profit margins.• Analyzed customer behavior through RFM analysis and K-Means clustering, delivering actionable insights that improved retention by 15% and enhanced marketing segmentation for ecommerce brands.• Utilized Amazon Marketing Cloud (AMC) to equip brands with deep insights into customer behavior, analyzing the advertising funnel, attribution, and brand searches helped in more visibility to enhance strategies and customer engagement.Awards: Outstanding Performance for exceptional performance and quality deliverables.

Analytics partner for Home Services, Financial Services, and NGOs. Point of Contact to clients.• Architected and implemented end-to-end ETL pipeline using Azure Data Factory and Logic Apps, integrating data from multiple REST APIs with OAuth 2.0 authentication, which reduced data processing time by 40%.• Designed and optimized Power BI dashboards for real-time business analytics, integrating data from a scalable Azure SQL Server data warehouse with star schema modeling, improving decision-making speed by 60% with actionable insights.• Enabled informed executive decisions by developing and delivering intuitive interactive Power BI reports, offering comprehensive insights into finance operations for key stakeholders.• Optimized workforce deployment for a home services brand by developing a demand-forecast model by leveraging historical weekly patterns to derive an optimal workforce size, resulting in a significant reduction in operational costs.• Established a data warehouse by designing robust data models and implementing ETL pipelines. These pipelines fueled daily operational reports, enhancing data-driven decision-making processes.Awards: Spot Recognition Award - the Outstanding Performer for quality deliverables in effective time across multiple projects.

Analysis and reports on the Call Center Operations and its driving factors - Provided the end-to-end Business Intelligence solution.• Enhanced visibility into call center operations by modeling the data and creating Power BI reports, delivering a comprehensive BI solution for improved decision-making.• Crafted interactive end-to-end dashboards, deriving key business metrics and influential factors, leading to improved strategies, resulting in a 14% enhancement in service levels and an 8% reduction in average waiting times.

• Utilized SQL and Power BI with advanced DAX calculations to perform RFM analysis, CLTV, and churn rate, driving a 25% increase in customer retention and a 15% rise in average order value (AOV).• Created dynamic Power BI dashboards to visualize customer insights and purchase patterns, enabling data-driven decisions that resulted in an 18% revenue growth within six months.