Intern, Supply Chain (Data Insights and Profitability), (Winter 2027)
- Dorval, QC, Canada
Volunteer
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Job details
- Job type
- Volunteer
- Apply by
- Experience
- You have at least 2 years of experience in developing and deploying machine learning models in an academic setting.
- Posting language
- English
- Posted
Original job description
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
- Bombardier Products conference
- Visits of the Bombardier sites
- Bombardier Academy of Learning
- Volunteering
- Networking for Success
- 5 à 7, Potluck, and much more!
- 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.
- 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.
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.
- Location: Administrative Centre (CA)
- Duration: 4 months
- Flexible workplace-Hybrid
More about this job
Responsibilities
Develop machine learning models and analytics tools using ERP data to forecast demand, optimize inventory and procurement, and detect anomalies in invoices, ordering policies, and budgets. Build reporting tools and dashboards, collaborate with stakeholders and management to address business needs, and present findings on supply chain performance and key metrics.
Requirements
Applicants must be current students pursuing a degree in data science, business analytics, computer science, mathematics, statistics, engineering, or a related field, with at least two years of academic experience developing and deploying machine learning models. They should have strong programming and machine learning skills, experience with relevant data and cloud tools, effective communication skills, and the ability to work in English and French; familiarity with SAP, Microsoft Access, and reinforcement learning is an asset.
Skills
- Machine Learning
- Demand Forecasting
- Data Analysis
- Data Visualization
- Power BI
- Python
- SQL
- R
- Statistical Modeling
- Anomaly Detection
- Pattern Recognition
- TensorFlow
- PyTorch
- Scikit-Learn
- Azure
- AWS
Benefits
- Networking Opportunities
- Professional Development
- Learning Conferences
- Site Visits
- Volunteering Opportunities
Visa sponsorship
Not detected in the job text
Categories
- Data & Analytics
- Logistics
- Technology
- Software
- Finance & Accounting
Keywords
- Supply Chain Management
- Aerospace
- Artificial Intelligence
- Machine Learning
- Demand Forecasting
- ERP Data
- Inventory Optimization
- Procurement
- Power BI
- Data Visualization
- Invoice Anomaly Detection
- Pattern Recognition
- Statistical Modeling
- Python
- Pandas
- R
- SQL
- Complex Queries
- TensorFlow
- PyTorch
- Scikit-Learn
- Azure
- Databricks
- Synapse
- AWS
- PySpark
- Azure DevOps
- CI/CD
- MLflow
- SAP