
Nooshin Hamidian
AI & Analytics Coach | Turning Complex Data into Scalable Business Sol
Studied at University of Tennessee, Knoxville
Works at FedEx
Questions? Start chatting with this coach before you get started.
Nooshin's Offerings
Custom hourly · $175/hr
Get help with AI Automation, AI Fundamentals, and
Nooshin’s AI for Data & Analytics Qualifications
Experience level: Manager
Welcome to my profile! I bring a combination of deep academic rigor and hands-on industry impact to AI for Data & Analytics coaching. Holding a Ph.D. in Industrial Engineering and more than 6 years of experience solving complex, large-scale problems at FedEx, I have designed and deployed advanced AI/ML models, machine learning systems, and AI-driven solutions that directly improve operational efficiency and decision-making. My work spans the full lifecycle, framing ambiguous business problems, building mathematical and ML models, developing scalable data pipelines, and productionizing solutions with MLOps. Hands-on experience includes developing internal AI chatbots (RAG-based) to unlock enterprise knowledge, as well as consistently leveraging AI for automation and end-to-end workflow optimization across scheduling, planning, and decision systems. Proven impact includes improving predictive performance by up to 40%, enhancing optimization algorithms, and leading cross-functional initiatives that influence enterprise strategy. Strong communication skills enable me to translate highly technical concepts into clear, actionable insights for diverse audiences. Clients can expect not only technical guidance, but also a practical, results-driven approach to thinking critically about data, designing scalable solutions, and delivering measurable business value.
Nooshin can help with:
AI Automation
AI Fundamentals
AI Model Evaluation
Dashboard Creation
Data Cleaning & Prep
Data Pipeline Automation
Data Strategy
Data Visualization
Freelancing
Natural Language Querying
Predictive Analytics
Reporting & Insights
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
Nooshin has helped Leland clients get into Arizona State University