Lead engineer for labor management system that serviced over 10,000+ active internal users across all 30+ Walmart fulfillment centers. The labor management system allowed users to interact and make actionable insight through the data available on the application.• Developed multiple key features for application resulting in 30% time savings for users’ day-to-day operations• Drove database performance tuning through indexing and scheduled defragmentation• Mentored 2 software engineers, improving team productivity and knowledge sharing• Created RESTful APIs for internal analytics and data science teams to build dashboards and other applications• Liaised between engineers, product managers, and stakeholders for streamlined product planning• Created documentation for engineers that allowed fast onboarding and ability to contribute to code base quickly

Architected and created labor management system used across all Walmart fulfillment centers. The application replaced Walmart's legacy labor management system with a web application using Python and Django. • Designed and implemented labor management system that had an annualized savings of $80M• Used Django for frontend/backend of web application• Built web application frontend primarily using Python, Django, HTML, CSS, JQuery, and AJAX
• Designed data engineering pipelines using Kubernetes, Docker, and Cron
• Built robust and easily understandable database schema in data warehouse for internal data consumers

Managed labor management system that serviced over 2000+ active internal users across 14 fulfillment centers
. Designed proof of concept algorithms for warehouse management system's processes. • Created analytics dashboards to extrapolate key metrics to mid-senior level management • Designed picking algorithm for Walmart fulfillment center that optimized on customer SLAs and throughput • Led meetings with stakeholders to gather business requirements and partner on implementation process

Northeast regional process engineer responsible for benchmarking outbound departments across 8 Amazon sortable fulfillment centers. Served as technical lead for process engineering team of 50+ engineers which involved maintaining a database, data engineering pipelines, and creating dashboards and reports. • Benchmarked 8 fulfillment centers’ productivity through process improvement projects and manager consulting• Consulted and mentored mid-senior level leaders on best practices to to optimize key KPIs• Technical lead for database management and reporting used across all NA Amazon sortable fulfillment centers

• Immersive data science program tackling real world projects by implementing statistical and ML models in Python• Utilized boosting, feature engineering, and regularization to create model predicting sales prices of real estate• Created models to classify and categorize images of clothes with Keras and Convolutional Neural Networks• Used Natural Language Processing to analyze Twitter tweets and make predictions based on parsed data• Cleaned and wrangled data using Beautiful Soup and utilized APIs to import JSON files to Pandas dataframes

• Supplier Business Analyst for over 200 accounts that constituted to over $325,000 in monthly revenue• Improved QC process for false negatives by over 50% leading to better customer experience• Utilized SQL for data mining and customer case resolution

• Managed a team to increase efficiency by 20% and reduce human error in a production setting• Used time studies, flow charts, network diagrams and process maps to measure system• Designed unique racks and workstations with human factors and work measurements• Applied Lean Six Sigma principles and implemented 5S to maximize efficiency and eliminate waste• Standardized manual packaging procedure to reduce time variability and create takt time

• Utilized VBA in Microsoft Excel to efficiently gather from large pools of data• Performed linear regressions to analyze impact of relevant categories against the market• Extensively used the Bloomberg Terminal to pull data and analyze market trends