We are seeking enthusiastic and driven interns to join our AI/ML and Advanced Analytics team. This internship offers an opportunity to work on cutting-edge projects involving machine learning, artificial intelligence, advanced analytics, and data science. You will gain hands-on experience developing and deploying AI-driven solutions for real-world applications in domains such as payments systems, advanced analytics, and edge AI hardware.
Develop and deploy advanced machine learning models for predictive analytics, anomaly detection, and optimization in business-critical systems, such as payments platforms and supply chains.
- Design and implement analytical pipelines to process structured and unstructured data, supporting real-time decision-making and insights generation.
- Build models for predictive maintenance, customer behavior analysis, fraud detection, and operational efficiency improvement.
- Leverage advanced statistical methods and machine learning techniques (e.g., regression, classification, clustering, deep learning) to solve complex business problems.
- Integrate ML models with analytics platforms and visualization tools for actionable insights delivery.
- Collaborate with data engineers to ensure data pipelines are robust, scalable, and optimized for ML model training and deployment.
- Monitor and retrain deployed models to ensure they meet performance and accuracy benchmarks over time.
- Conduct exploratory data analysis (EDA) to uncover trends, correlations, and insights that inform strategic decision-making.
- Apply natural language processing (NLP) techniques for text analytics, sentiment analysis, and document classification.
- Ensure compliance with data privacy and security regulations in all analytics workflows.
This position is open to applicants who
reside in Toronto or Montreal and is
open to applicants seeking a 12 months
internship work term, commencing in May
2025. It is mandatory that all applicants are
enrolled in full-time studies at a post-
secondary institution and returning to full-
time studies upon completion of their work
term
- Proficiency in Python, R, or Java for AI/ML model development and testing
- Strong data modeling skills, including the ability to design and implement normalized and denormalized schemas
- Proficiency in encryption technologies and secure data handling, including experience with encryption protocols, data masking, and access control mechanisms
- Experience with data integration tools and frameworks for real-time and batch data processing
- Knowledge of cloud platforms and cloud-native database services, including serverless computing, data lakes, and containerized data workloads.
- Strong troubleshooting skills to identify and resolve performance, integration, and data quality issues in complex data ecosystems
- Ability to work effectively with cross-functional teams, ensuring that data solutions meet business and technical requirements
- Familiarity with data governance practices, ensuring compliance with data privacy regulations and standards
Create up to 3 bullets max (encouraging then to focus on required skills)