Analyst, Strategy and Business Development at Bombardier | Jobyssey

What are your contributions to the team?

Contribute to the improvement of current inventory algorithms and planning logic by analyzing reorder points, demand variability, forecast bias, consumption patterns and inventory segmentation.
Ensure the quality, reliability and governance of inventory and master data used for inventory decisions, reporting, forecasting models and future AI-enabled tools.
Validate ERP and planning data, identify anomalies, investigate root causes and recommend corrective actions to improve data integrity across sites and systems.
Support the development, testing and monitoring of forecasting, replenishment and inventory recommendation models, including machine learning and AI-enabled decision-support tools.
Review AI-generated recommendations before operational deployment to ensure outputs are explainable, aligned with business rules and supported by appropriate human oversight.
Develop and maintain automated dashboards, Power BI reports, executive scorecards and inventory KPIs to monitor inventory levels, forecast accuracy, excess and obsolete inventory, shortages, turns, service levels and material flow performance.
Collaborate with Material Logistics, Planning, Operations, Finance, IT, Data Science and Digital Transformation teams to translate business needs into analytical and digital solutions.

Apply SQL, Python, Excel, Power Query and other analytical tools to extract, transform, analyze and automate inventory data processes.
Support Bombardier’s transition from manual or rule-based planning activities toward more automated, predictive and AI-assisted ways of working.
Participate in pilots and continuous improvement initiatives related to demand forecasting, inventory optimization, exception management, anomaly detection and digital inventory control.
Document assumptions, model inputs, business rules, data definitions and decision logic to ensure consistency, traceability and governance.
Present analytical findings, model outputs, risks, trade-offs and recommended actions clearly to technical and non-technical stakeholders.
Stay current on advancements in AI, machine learning, supply chain analytics, forecasting and inventory optimization, and help identify practical use cases for Bombardier.

How to thrive in this role?

Bring at least 2 years of experience in inventory analysis, supply chain analytics, business analytics, data analysis, logistics, planning, finance analytics, or a related field.
Hold a bachelor’s degree in Supply Chain, Logistics, Industrial Engineering, Business Analytics, Data Science, Computer Science, Mathematics, Statistics, or a related discipline.
Have experience working with ERP systems, planning tools, business databases, and operational data sources.
Develop dashboards, management reports, automated reporting flows, and performance scorecards.
Demonstrate advanced Excel skills, including pivot tables, Power Query, Power Pivot, formulas, data modeling, and dashboard development.
Demonstrate advanced Power BI skills, including interactive dashboards, executive scorecards, trend analysis, KPI monitoring, and automated reporting.
Have intermediate to advanced SQL knowledge, including data extraction, transformation, joins, query development, and validation of large datasets.
Have basic to intermediate knowledge of data warehouses and cloud-based analytics platforms such as Microsoft Azure Synapse Analytics, Azure Data Lake, and Databricks.
Understand artificial intelligence and machine learning concepts, including predictive analytics, anomaly detection, forecasting models, and recommendation logic.
Apply Microsoft Copilot and Generative AI tools responsibly to support data analysis, reporting, documentation, and process improvement.
Interpret AI-assisted outputs with business judgment, ensuring recommendations are explainable, reliable, and aligned with inventory planning rules.
Have exposure to forecasting, inventory management, material planning, replenishment, master data, logistics, or supply chain planning.

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