Nooshin Hamidian
Studied at University of Tennessee, Knoxville
Works at FedEx
Successful clients at
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Work Experience
Operations Advisor
FedEx
October 2022 - Present
Interviewer
● Developed and maintained scalable data pipelines and tools in collaboration with developers, facilitating the transformation of big data into insightful, actionable outputs for strategic decision-making during month trip scheduling. ● Developed a Retrieval Augmented Generation (RAG) bot to retrieve information from internal documents, including PDF and PowerPoint (PPT) formats. ● Developed AI-powered automation for flight scheduling and travel itinerary planning. ● Enhanced a heuristic algorithm for identifying FedEx pilot requirements by fiscal year. ● Developed an optimization algorithm to find the optimum vehicle size at each route. ● Developed a fuel consumption forecasting model that captured stage-specific flight dynamics to improve prediction accuracy across all phases of flight. ● Developed Power BI dashboards to monitor ML model performance, enabling agile adjustments to metrics in response to evolving business needs. ● Developed an algorithm to improve at-stop delivery time window with outputs close to optimal solutions. ● Analyzed high-volume data to enable data-driven decision-making and improve efficiency in monthly trip scheduling operations. ● Developed a recommender systems applying neural collaborative filtering model in TensorFlow to recommend trips for pilots in each bidding period. ● Implemented MLOps monitoring process and deployed monitoring data pipelines in Azure to track model performance, product metrics and data quality KPIs post-production. ● Led cross-functional projects that gathered data from diverse sources directly impacting organizational strategies for the number of rentals and annual fleet planning.
Operations Advisor
FedEx
May 2021 - Present
Interviewer
● Led a project to find the probability of trip cancelation per bidding period using mathematical modeling and machine learning. ● Leveraged highly imbalanced trip datasets using techniques such as cluster modeling. ● Developed recommender systems to estimate pilots' preferences in bidding periods. ● Evaluated multiple solutions for anomaly detection to estimate the at-stop time window more accurately.
Operations Research Analyst
FedEx
April 2020 - Present
Interviewer
● Enhanced accuracy of an existing vehicle recommendation algorithm by 25%. ● Developed a forecasting model to predict the number of Max vehicles On-Road (MOR) and improved the performance by applying stacking machine Learning models such as gradient boosting and random forest. ● Enhanced predictive modeling that outperformed traditional approaches by 40%, using advanced statistical methods and machine learning techniques.
Graduate Research Assistant
University of Tennessee, Knoxville
August 2015 - December 2019
Admissions Committee
● Developed a two-stage stochastic MILP model to optimize production planning and operational flexibility. ● Built a correlation-based optimization model for mixed bundling in marketing analytics. ● Implemented a pruning algorithm for large-scale bundling problems that outperformed rule-mining ML approaches. ● Secured and managed $300K+ in DLA-funded supply chain data science projects while leading a team of five graduate students. ● Mentored 40+ international students in Lean Summer Programs across organizations including Denso, Covenant Health, and Kelsan. ● Led experimental design analytics projects to evaluate milk container quality for the Defense Logistics Agency (DLA).
ERP Consultant
Semester at Sea
2011 - Present
● Led a 5-member team to deliver supply chain and ERP solutions that improved operational efficiency and customer satisfaction
Education
University of Tennessee, Knoxville
Doctor of Philosophy - PhD, Industrial Engineering
Grade: 4.0
University of Tennessee, Knoxville
Master's degree, Statistics
Grade: 4.0
Sharif University of Technology
Master's degree, Industrial Engineering
Khajeh Nasir Toosi University of Technology
Bachelor's degree, Industrial Engineering
12 Reviews
Overall Rating
5.0
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