Pedram Farghadani

Pedram Farghadani

Data Scientist focused on optimization, forecasting, and AI decision support

Professional Experience

Data Scientist

Yeji Data Lab, Montreal, QC
Sep 2025 – Present

  • Develop optimization-driven decision-support workflows for business and operational planning problems.
  • Apply operations research methods to structure complex planning needs into practical, scalable models.

Data Scientist

DataSphere Lab | McGill University, Montreal, QC
Jul 2025 – Sep 2025

  • Analyzed large-scale transactional sales data from Infasco for industrial demand-planning use cases, including cleaning, anomaly detection, and outlier treatment.
  • Built and evaluated demand forecasting models using XGBoost and LightGBM to support sales-planning decisions.
  • Engineered temporal and categorical features, tuned models, and assessed performance using RMSE and SMAPE to improve predictive accuracy.

Operations Research Specialist

CIRRELT, Montreal, QC
Jan 2021 – Sep 2025

  • Built a Retrieval-Augmented Generation (RAG) system using LangChain, Azure OpenAI embeddings, and FAISS to retrieve disaster-planning context and answer technical user queries, with fallback search and query-classification logic. ▶️ Demo: RAG for ACFs
  • Developed a Streamlit and LangChain AI assistant for hospital evacuation planning that interprets free-text queries, extracts planning parameters, and invokes a backend optimization engine. Integrated with Azure OpenAI and dynamic user feedback.
    ▶️ Demo: LLM for ACFs
  • Designed reinforcement learning models, including Q-Learning and Deep Q-Learning, combined with ALNS to support decision-making under uncertainty in disaster management and resource allocation settings.
  • Developed a Stochastic Dual Dynamic Programming (SDDP) algorithm for multi-stage stochastic optimization in casualty response and medical-resource allocation.
  • Applied scenario clustering methods such as K-means++ and Self-Organizing Maps, and benchmarked optimization methods including Benders decomposition and Progressive Hedging for large-scale planning problems.

Teaching Assistant

Concordia University, Montreal, QC
Fall 2024 – Winter 2025

  • Served as Teaching Assistant for Scheduling Theory and Quantitative Methods in Healthcare Systems, under the supervision of Prof. Hossein Hashemi Doulabi, providing support to students in their coursework and projects.

Lab Demonstrator

Concordia University, Montreal, QC
Fall 2024

  • Assisted Prof. Gerard Gouw in delivering and managing labs for the course Human Factors Engineering, ensuring smooth execution of laboratory sessions with more than 30 students.

Software Trainer

FaraDars Educational Institution, Tehran, Iran
Summer 2019

  • Developed and designed an online course titled How to Balance a Production/Assembly Line using the Flexible Line Balancing (FLB) Software.
  • Facilitated the enrollment and successful completion of over 900 students in the course.