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Intern, Supply Chain (Data Insights and Profitability), (Winter 2027)

Pay
Pay not listedSimilar roles state $118K–$194K
Work setting
Not stated
Employment
Not stated

Before you apply

New graduates
For current studentsJob title: Intern, Supply Chain (Data Insights and Profitability), (Winter 2027) (Dorval, Québec, CA, H4S 1Y9)

What you’ll work on

Full posting
  • Develop demand forecasting models from ERP data to guide inventory and procurement

  • Apply machine learning to predict likely errors in invoices, ordering policies and budgets

  • Build Power BI reports and KPI tools tracking forecast accuracy and inventory

  • Present findings clearly to stakeholders and upper management

From the employer’s posting
Utilize ERP data and data science techniques to develop demand forecasting models
Apply machine learning algorithms to identify patterns and predict likely errors in invoices, ordering policies, and budgets
Collaborate with stakeholders to construct customer-facing reporting tools that provide insights and metrics tracking forecast accuracy, inventory levels, transportation efficiency, and other key performance indicators (KPIs).
Present findings in a clear and compelling manner to stakeholders.
Apply at Bombardier

Posting record

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Actively hiringFirst seen by us 4 days ago, still listed, and not a repost of an earlier posting.

Status in our records
Live
First seen by us
Nov 5, 20264 days ago
Recorded sightings
5
Last seen by us
Nov 9, 2026

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.

How this job compares

Pay

$118K–$194K is typical

The middle half of what similar US postings state. This one doesn’t list pay.

From 3,819 postings in the last year. Stated ranges, not salaries paid.

Time since we first saw it

Day 4

Early. Similar jobs usually come down between day 7 and day 57.

From 10,789 similar postings that came down. Coming down is not always a hire.

Bombardier is hiring

13 open jobs

Open jobs by the week we first saw them, last 12 weeks.

Hiring record

See how this role fits your experience

Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.

  • Python
  • R
  • SQL
  • AWS
  • Azure
  • Databricks
  • MLflow
  • Power BI
  • pandas
  • PySpark
  • PyTorch
  • scikit-learn
  • TensorFlow
Where the posting names them
- You have at least 2 years of experience in developing and deploying machine learning models in an academic setting. - Strong programming skills in languages such as SQL, Python, R, or similar, with a focus on developing scalable and efficient AI solutions. - Demonstrated academic or project experience working as a data scientist, AI engineering, or in a similar role, with a strong focus on developing AI tools and algorithms would be a strong asset.
- You have strong knowledge of machine learning algorithms, statistical modeling, and data analysis techniques at the undergraduate level. - You have hands-on experience with programming languages such as Python, Pandas, R, SQL: Experience with complex queries. - You have In-depth understanding of machine learning algorithms, techniques, and frameworks. Candidates should be proficient in designing, training, and evaluating machine learning models using tools such as TensorFlow, PyTorch, scikit-learn, etc.
- You have In-depth understanding of machine learning algorithms, techniques, and frameworks. Candidates should be proficient in designing, training, and evaluating machine learning models using tools such as TensorFlow, PyTorch, scikit-learn, etc. - You have experience in development using cloud providers Azure (Databricks, Synapse) and AWS. - You have some knowledge of Pyspark and AzureDevops or equivalents for CICD orchestration.
- You have some knowledge of Pyspark and AzureDevops or equivalents for CICD orchestration. - You have experience at some level with some production-level ML lifecycle management, at least with MLflow. - You have strong communication and interpersonal skills to work effectively with cross-functional teams.
- Utilize ERP data and data science techniques to develop demand forecasting models, enabling the company to anticipate customer demand, optimize inventory levels, and streamline procurement processes. - Leverage Power BI for data visualization and reporting. - Apply machine learning algorithms to identify patterns and predict likely errors in invoices, ordering policies, and budgets enabling the company to reduce rework and improve financial accuracy.
- You have experience in development using cloud providers Azure (Databricks, Synapse) and AWS. - You have some knowledge of Pyspark and AzureDevops or equivalents for CICD orchestration. - You have experience at some level with some production-level ML lifecycle management, at least with MLflow.
- You have hands-on experience with programming languages such as Python, Pandas, R, SQL: Experience with complex queries. - You have In-depth understanding of machine learning algorithms, techniques, and frameworks. Candidates should be proficient in designing, training, and evaluating machine learning models using tools such as TensorFlow, PyTorch, scikit-learn, etc. - You have experience in development using cloud providers Azure (Databricks, Synapse) and AWS.

Your next step

Complete your application on jobs.bombardier.com. The employer’s form will show what is required.

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Demand for Data Scientist roles

New Data Scientist postings at the employers we follow are down 5% over the last 6 weeks compared with the 6 before.

Weekly new Data Scientist postings at the same employers, from the week of August 17 to the week of November 2. The fewest in a week was 1,408, the most 2,964, and the latest week had 2,139.
August 17Last week

Each bar is one week of new postings. The darkest bars are the last 6 weeks.

Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.

About the role

We file this job under Data Scientist, by the work the posting describes.

Data scientists use statistics and models to answer harder questions, such as whether a change worked, what demand will look like next quarter, or which customers are likely to leave.

Postings usually ask for Python or R, SQL, statistics, experiment design and common machine learning methods.

Unlike an ML engineer, a data scientist's main output is often an analysis or a first model, not software running inside a product.

US government figures for data scientists

Median yearly pay, May 2025
$120,230
Expected change, 2025 to 2035
34.6% more jobsagainst 3.5% for all jobs

Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-2051.

Job description

View original posting ↗

Innovation is in our DNA… is it in yours?
Bombardier is a global leader in aviation, creating innovative and game-changing planes. Our products and services provide world-class experiences that set new standards in passenger comfort, energy efficiency, reliability and safety. We are a global organization focused on working together with a team spirit.

Your boarding pass will include… 

Several conferences, including:

  • Meet An Executive
  • Women Taking Flight

Learning more about Bombardier, including:

  • Bombardier Products conference 
  • Visits of the Bombardier sites 
  • Bombardier Academy of Learning 

Many social/networking opportunities, including:

  • Volunteering 
  • Networking for Success
  • 5 à 7, Potluck, and much more!
     

What You Will Learn

  • Gain experience in applying AI and ML in a real-world business setting.
  • Learn about supply chain management and the aerospace industry.
  • Learn from experienced professionals in applying analytics in the workplace.
  • Be exposed to management to learn about their business priorities.
  • Learn about financial concepts that are important for managing a global business.

What are your contributions to the team?

  • Utilize ERP data and data science techniques to develop demand forecasting models, enabling the company to anticipate customer demand, optimize inventory levels, and streamline procurement processes. 
  • Leverage Power BI for data visualization and reporting. 
  • Apply machine learning algorithms to identify patterns and predict likely errors in invoices, ordering policies, and budgets enabling the company to reduce rework and improve financial accuracy. 
  • Hands-on pattern recognition and anomaly detection ML solutions. 
  • Collaborate with stakeholders to construct customer-facing reporting tools that provide insights and metrics tracking forecast accuracy, inventory levels, transportation efficiency, and other key performance indicators (KPIs). 
  • Manage the development of tools to increase efficiencies throughout the team. 
  • Present findings in a clear and compelling manner to stakeholders.
  • Work in members of upper management to diagnose problems, identify business needs, and develop solutions and tools that meet their needs.

How to thrive in this role?

As our ideal candidate:

  • You are studying a degree in data science, business analytics, computer science, mathematics, statistics, engineering or a related field. 
  • You have at least 2 years of experience in developing and deploying machine learning models in an academic setting. 
  • Strong programming skills in languages such as SQL, Python, R, or similar, with a focus on developing scalable and efficient AI solutions. 
  • Demonstrated academic or project experience working as a data scientist, AI engineering, or in a similar role, with a strong focus on developing AI tools and algorithms would be a strong asset. 
  • You have strong knowledge of machine learning algorithms, statistical modeling, and data analysis techniques at the undergraduate level. 
  • You have hands-on experience with programming languages such as Python, Pandas, R, SQL: Experience with complex queries. 
  • You have In-depth understanding of machine learning algorithms, techniques, and frameworks. Candidates should be proficient in designing, training, and evaluating machine learning models using tools such as TensorFlow, PyTorch, scikit-learn, etc.  
  • You have experience in development using cloud providers Azure (Databricks, Synapse) and AWS. 
  • You have some knowledge of Pyspark and AzureDevops or equivalents for CICD orchestration. 
  • You have experience at some level with some production-level ML lifecycle management, at least with MLflow. 
  • You have strong communication and interpersonal skills to work effectively with cross-functional teams. 
  • Familiarity with Microsoft Access and SAP and Reinforcement Learning is considered an asset.
  • You are able to work effectively in English and French on a daily basis.
  • You are able to work onsite at the designated Montreal office location, at least two (2) days per week, sometimes more, as per the applicable policy.

​
Boarding Information:

  • Location: Administrative Centre (CA)
  • Duration: 4 months
  • Flexible workplace-Hybrid

It is important to note that our internship opportunities are open to students only, not new graduates. All our interns may be required to occasionally travel outside of Canada for training/work purpose.

​

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Pay

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Location & working pattern

Dorval, Québec, CA, H4S 1Y9

- Duration: 4 months - Flexible workplace-Hybrid It is important to note that our internship opportunities are open to students only, not new graduates. All our interns may be required to occasionally travel outside of Canada for training/work purpose.
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