Xuanlong (Lincoln) Lyu

AI Researcher

Canada6 mos experience

Key Highlights

  • Achieved 266% ROI in forecasting system development
  • Improved forecast accuracy from 43% to 73%
  • Delivered interactive dashboards reducing report time significantly
Stackforce AI infers this person is a Data Scientist specializing in Demand Forecasting and Data Engineering within the SaaS industry.

Contact

LinkedIn

Skills

Core Skills

Demand ForecastingData EngineeringMachine LearningData VisualizationSql

Other Skills

PythonAzure DatabricksPower BIEnterprise Resource Planning (ERP)Time Series ForecastingMicrosoft Power BIMySQLR 语言

Experience

Mckesson canada

Data Scientist Intern

Sep 2024 – Apr 2025 · 7 mos · Montreal, Quebec, Canada · Hybrid

  • Built and deployed NeuralProphet demand forecasting models for OTC and CPG products, improving forecast accuracy from 43% to 73% and reducing MAPE from 56.57% to 25.18%.
  • Designed and implemented an automated Azure Databricks pipeline integrating unstructured data (holidays, weather, search trends), enabling real-time multi-horizon forecasts and reducing manual adjustments 40%.
  • Led the development of an end-to-end forecasting system, ensuring scalability and JDA compatibility, achieving 266% ROI within the McGill in-sample test portfolio.
  • Delivered interactive Power BI dashboards with 15 KPIs, including per-DC avoidable cost breakdown and model comparison views, reducing executive report preparation time from 3 days to same-day delivery.
Demand ForecastingData Engineering

Dali jinye business service

Intern

Jan 2023 – Mar 2023 · 2 mos · Dali, Yunnan, China · On-site

  • Reduced package damage rate by 5% through in-depth root cause analysis on automation systems, leveraging statistical process control to optimize sorting height parameters and workflow sequencing.
  • Redesigned and optimized logistics operational databases, applying indexing strategies and query optimization in SQL to improve data retrieval speed by 20% and enhance real-time reporting accuracy for network performance monitoring.
SQLPython

顺丰速运有限公司

Intern

Jan 2022 – Mar 2022 · 2 mos · Kunming, Yunnan, China · Hybrid

  • Reduced package damage rate by 5% through in-depth root cause analysis on automation systems, leveraging statistical process control to optimize sorting height parameters and workflow sequencing.
  • Redesigned and optimized logistics operational databases, applying indexing strategies and query optimization in SQL to improve data retrieval speed by 20% and enhance real-time reporting accuracy for network performance monitoring.
SQL

Education

McGill University - Desautels Faculty of Management

Master's degree — Master of Management in Analytics

Jul 2024 – Oct 2025

Kunming University of Science and Technology

Bachelor of Engineering - BE — Logistics Engineering

Sep 2019 – Jul 2023

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