Data Science Summer Student

Job Description:

Open to MRU Data Science StudentsProject Overview:De Havilland is seeking a senior capstone student or student team in Data Science, Computer Science, or a related discipline to develop a machine learning solution that predicts future parts requirements for scheduled maintenance events using historical maintenance and materials data.Scheduled maintenance activities are planned in advance, but the exact parts required can vary based on aircraft usage, age, configuration, maintenance history, and prior inspection findings. More accurate prediction of future parts demand would improve maintenance readiness, reduce delays, lower excess inventory, and support better materials planning. The objective of this project is to design, develop, validate, and demonstrate a production-ready system capable of forecasting likely part requirements for upcoming scheduled maintenance packages. Project Objectives:The student will be expected to:analyze historical maintenance and parts consumption data identify key drivers of parts demand for scheduled maintenance events develop machine learning models to predict likely part requirements and quantities evaluate model performance against baseline planning methods design and implement a production-ready solution architecture suitable for operational deployment provide recommendations for integration into maintenance planning and inventory support processes Expected Deliverables:The final project should include:a clearly defined problem statement and success criteria a cleaned, structured, and documented modeling dataset exploratory data analysis and feature engineering approach one or more predictive models for part demand forecasting validation results with business-relevant performance measures a production-ready system, including: repeatable data pipeline deployable model workflow documented system architecture version-controlled codebase error handling, monitoring, and retraining considerations final technical documentation and presentation to stakeholders QualificationsThis project is well suited to a capstone course in Data Science, Machine Learning, Computer Science, Software Engineering, or Industrial Analytics, particularly for students interested in applied AI, predictive maintenance, and operations optimization. SkillsPython for data analysis and machine learning SQL and data wrangling across multiple operational datasets Machine Learning Model Development and evaluation feature engineering and handling of real-world data quality issues software engineering practices for production deployment documentation and communication of technical work to business stakeholders Experience with time-based validation, imbalanced datasets, MLOps concepts, APIs, cloud deployment, dashboards, or maintenance/supply chain analytics would be considered an asset.

Job Ident #: 2200

Company Details

De Havilland Canada

123 Garratt Blvd
Toronto, Ontario M3K 1Y5 Canada
dehavilland.com

Throughout an impressive 75-year history of producing various models of aircraft in Canada and for the world, De Havilland has always proudly been known for its adaptability and dependability. Being responsible for creating some 3,500 aircraft—includ...

Supported Manufacturers:
De Havilland

Supported Models:
Dash 8-400

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Job Info

Location

Calgary, Alberta, Canada

Type

Permanent

Company Details

De Havilland Canada

123 Garratt Blvd
Toronto, Ontario M3K 1Y5 Canada
dehavilland.com