Analyst, Business Systems

In your role, you will

•    Collaborate with experienced Machine Learning Engineers (MLEs) to develop and deliver machine learning (ML) solutions that meet the needs of Bombardier's organization.
•    Assist in the deployment of ML models within the production data science environment, following best practices, pipeline controls, and maintaining clear documentation.
•    Contribute to the development of tools for monitoring the machine learning life cycle and providing observability into the system's execution flow.
•    Participate in designing, implementing, and optimizing maintainable and reusable ML services that enhance Bombardier's data and advanced analytics solutions.
•    Assist in analyzing, processing, and modeling data, and help interpret the results to create actionable plans that positively impact Bombardier's operations.
•    Work on configuring robust environments that handle data and microsystem connections, enabling ML workflows.
•    Collaborate with the Artificial Intelligence (AI) team members, learning agile project management methodologies (e.g., Scrum, Kanban) and application lifecycle management practices (e.g., test automation, configuration management).
•    Engage with users and business stakeholders to gather requirements and feedback to maximize value for the business units.
•    Contribute to implementing continuous integration and deployment methods to automate quality assurance and the delivery of new functionality to ML solutions users.
•    Provide support for troubleshooting/improving existing ML products.
 

As our ideal candidate

•    You hold a bachelor's or master's degree in Computer Science, Computer Engineering, Software Engineering, Statistics, or a related quantitative field.
•    You have experience and a strong interest in analytics, data science, and computer engineering.
•    You are familiar with, and open to gaining experience, using cloud computing platforms.
•    You have experience using Microsoft Azure’s advanced analytics tools (e.g., Azure Data Factory, Azure Databricks, Azure Machine Learning).
•    You developed machine learning algorithms before.
•    You are willing to learn about Docker and software packaging and ML production lifecycle.
•    You are familiar with software architecture, and modular software development. Proficiency with Python is a must. Familiarity with PySpark is a plus.
•    You have familiarity with Linux scripting or PowerShell scripting.
•    You are interested in agile project management and application lifecycle management, including familiarity with Azure DevOps or Gitlab.
•    You possess strong problem-solving and debugging skills.
•    You have strong written and verbal communication and presentation skills in English, and able to communicate in French.