Analyst, Data Science & AI

Bombardier Transportation GmbH; Dorval; Hybrid; CAD 90,000 - 130,000; Full time

Benefits offered by this job

Insurance plans

Retirement plan

Employee Assistance Program

Job summary

Bombardier Transportation GmbH is seeking an Analyst, Data Science & AI to develop applied ML solutions, forecasting, and optimization in a bilingual environment in Canada. You will profile data, build reproducible pipelines with Databricks and Azure, and partner with engineers to deploy models.

You will translate business needs into analytical targets, ensure robust validation, and communicate findings to stakeholders.

Qualifications

• Hold a bachelor’s degree in data science, computer science, statistics, mathematics, engineering, operations research, or a related quantitative field.
• Have 5+ years of experience developing applied data science, ML, forecasting, optimization, NLP, or risk-modeling solutions in business or enterprise environments.
• posses strong Python and SQL skills, with hands-on experience using pandas, NumPy, scikit-learn, Spark/PySpark, and Databricks.
• Can frame business problems into analytical targets, constraints, acceptance criteria, measurable outcomes, and production-ready recommendations.
• Apply sound model-development and validation practices, including baseline development, cross-validation, back-testing, error analysis, explainability, and KPI definition.
• Communicate clearly with technical and non-technical stakeholders, explaining assumptions, results, limitations, trade-offs, and recommended actions.
• Thrive in fast-paced, collaborative environments and are fluent in English and French, spoken and written.

Responsibilities

• Translate business challenges into measurable forecasting, optimization, NLP, retrieval, classification, risk, or recommendation problems.
• Explore, profile, and validate governed enterprise data.
• Develop reproducible feature-engineering, training, validation, and scoring pipelines using Databricks and Azure.
• Establish appropriate analytical baselines and business performance measures.
• Build and validate models using cross-validation, back-testing, uncertainty analysis, and business-relevant metrics.
• Develop document-intelligence and RAG solutions with grounded outputs, citations, retrieval evaluation, guardrails, and human review.
• Develop forecasting and inventory-optimization solutions that account for intermittent demand, uncertainty, service levels, and operational constraints.
• Develop classification and risk models using techniques for imbalanced data, calibration, explainability, and cost-sensitive decisions.
• Operationalize models using MLflow, model registries, automated testing, deployment controls, monitoring, drift detection, and retraining plans.
• Apply privacy, security, lineage, explainability, bias, robustness, auditability, and incident-response controls throughout the AI lifecycle.
• Clearly communicate assumptions, limitations, trade-offs, and recommendations; partner with engineers to productionize models.

Skills

Python

SQL

pandas

NumPy

scikit-learn

Spark/PySpark

Databricks

Education

Bachelor's degree in data science, computer science, statistics, mathematics, engineering, operations research, or related quantitative field

Tools

Databricks

Azure

MLflow

Job description

When applicable, Bombardier promotes flexible and hybrid work policies.

At Bombardier, we design, build and maintain the world’s peak-performing aircraft for the world’s most discerning people and businesses, governments and militaries. We have been successful in setting the highest standards by putting our people at the heart of it all, and defining excellence, together.

Working at Bombardier means operating at the highest level. Every day, you are part of a team that delivers superior experiences and products, pushing the boundaries of what's possible in our industry and beyond. By prioritizing employee growth and development, we empower everyone to reach their full potential on their own terms, because the best work happens when you are free to be yourself and share your unique expertise.

With our employees’ well-being top of mind, we offer a comprehensive and competitive Benefits Program, which includes the following:

• Insurance plans (Dental, medical, life insurance, disability, and more)


• Retirement savings plan


• Employee Assistance Program

What are your contributions to the team?

• Translate business challenges into measurable forecasting, optimization, NLP, retrieval, classification, risk, or recommendation problems.


• Explore, profile, and validate governed enterprise data.


• Develop reproducible feature-engineering, training, validation, and scoring pipelines using Databricks and Azure.


• Establish appropriate analytical baselines and business performance measures.


• Build and validate models using cross-validation, back-testing, uncertainty analysis, and business-relevant metrics.
  


• Develop document-intelligence and RAG solutions with grounded outputs, citations, retrieval evaluation, guardrails, and human review.


• Develop forecasting and inventory-optimization solutions that account for intermittent demand, uncertainty, service levels, and operational constraints.


• Develop classification and risk models using suitable techniques for imbalanced data, calibration, explainability, and cost-sensitive decisions.


• Operationalize models using MLflow, model registries, automated testing, deployment controls, monitoring, drift detection, and retraining plans.


• Apply privacy, security, lineage, explainability, bias, robustness, auditability, and incident-response controls throughout the AI lifecycle.


• Clearly communicate assumptions, limitations, trade-offs, and recommendations. Partner with full stack and platform engineers to integrate models into production workflows and user experiences.


• Maintain model documentation, validation evidence, monitoring plans, and support procedures.


• Partner with cross-functional business, technology, data, governance, and delivery stakeholders across the enterprise.


• Translate business requirements into maintainable technical designs and acceptance criteria.

How to thrive in this role?

• You hold a bachelor’s degree in data science, computer science, statistics, mathematics, engineering, operations research, or a related quantitative field.


• You have 5+ years of experience developing applied data science, machine learning, forecasting, optimization, NLP, or risk-modeling solutions in business or enterprise environments.


• You have strong Python and SQL skills, with hands-on experience using pandas, NumPy, scikit-learn, Spark/PySpark, and Databricks.


• You can frame business problems into analytical targets, constraints, acceptance criteria, measurable outcomes, and production-ready recommendations.


• You apply sound model-development and validation practices, including baseline development, cross-validation, back-testing, error analysis, explainability, and business KPI definition.


• You communicate clearly with technical and non-technical stakeholders, explaining assumptions, results, limitations, trade-offs, and recommended actions.


• You thrive in fast-paced, collaborative environments and are fluent in English and French, spoken and written.

Please note: You don’t need all the skills, knowledge, and experience listed to apply for this position. We’re not looking for the perfect candidate, we’re looking for great talent and passionate individuals.
Bombardier is an equal opportunity employer and encourages persons of any race, religion, ethnicity, gender identity, sexual orientation, age, immigration status, disability or other applicable legally protected characteristics to apply.

Job Analyst, Data Science & AI

Primary Location Administrative Centre (CA)

Organization Aerospace Canada

Shift Day job

Employee Status Regular

Requisition 14734 Analyst, Data Science & AI