Analyst, Data Science & AI
Bombardier is hiring an Analyst, Data Science & AI. Level rates it ; you can apply on Bombardier.
Level's read on this job
- Level rates this role Builds AI ●●●●: the job is building AI systems.
- The posting mentions scikit-learn, MLflow and Databricks among its tools and skills.
- Level classes it as a senior role.
- Bombardier has 1,000+ other open roles on Level.
AI in this role
When applicable, Bombardier promotes flexible and hybrid work policies.
Why join us?
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.
Bombardier’s Benefits Program
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)
- Competitive base salary
- Retirement savings plan
- Employee Assistance Program
- Tele Health 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.
Now that you can see yourself in this role, apply and join the Bombardier Team!
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
How we rate this
Analyst, Data Science & AI at Bombardier rates 83 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.
Builds AI. The job is building AI systems.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Questions you could be asked
- How would you design a retrieval step so the model answers from real data instead of guessing?
- What NLP problem have you worked on, and how did you measure whether it actually worked?
- What are the limits of scikit-learn that you've run into, and how did you work around them?
- What's a project where you used MLflow hands-on?
- Walk me through how you've used Databricks in your day-to-day work.
Adapt your resume
- List these exact terms on your resume: RAG, NLP, scikit-learn, MLflow, and Databricks. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.
Want an expert to read your CV for this job?
Free. Send your CV and the role you want next. We reply by email within 2 to 4 business days.
Get new data jobs (Builds AI ●●●●) by email
One email a week with the new data jobs (Builds AI ●●●●), each rated for how much AI is in the work. No recruiter spam, unsubscribe in one click.
Free. One email a week. Unsubscribe in one click.
Similar roles
Data roles that build AI, at other companies.
What kind of AI work fits you?
Answer 12 practical questions in about three minutes. Get a simple profile, the work it points to, and live roles to explore next.
Find my next step