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.