IBM Payments Centre Machine Learning Developer Intern
IBM
Job Overview
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Job Description
Introduction
IBM is seeking enthusiastic and driven interns to join our AI/ML and Advanced Analytics team. This internship offers hands-on experience working on cutting-edge projects, including developing innovative machine learning, artificial intelligence, advanced analytics, and data science solutions for real-world applications within payment systems and beyond.
Your Role And Responsibilities
- Develop and deploy advanced ML models for predictive analytics, anomaly detection, and optimization.
- Design analytical pipelines for processing structured and unstructured data.
- Build models for predictive maintenance, fraud detection, and customer behavior analysis.
- Utilize statistical methods and techniques including regression, classification, clustering, and deep learning.
- Integrate ML models with analytics platforms and visualization tools.
- Collaborate with data engineers to ensure robust and scalable data pipelines.
- Monitor and retrain models for performance and accuracy.
- Conduct exploratory data analysis to inform strategic decisions.
- Implement NLP techniques for text analytics, sentiment analysis, and document classification.
- Ensure compliance with data privacy and security regulations.
Preferred Education & Requirements
This internship is available to full-time post-secondary students (excluding MBA and PhD candidates) and requires proficiency in Python, R, or Java. Strong data modeling, encryption, data integration, cloud platform knowledge, and troubleshooting skills are essential.
Internship Details
This is an 8-month internship position starting in May 2026, located in Toronto.
Key skills/competency
- Machine Learning
- AI
- Advanced Analytics
- Data Science
- Predictive Analytics
- NLP
- Data Modeling
- Cloud Platforms
- Statistical Analysis
- Data Security
How to Get Hired at IBM
- Customize your resume: Highlight AI/ML and data analytics skills.
- Showcase projects: Detail any machine learning or analytics work.
- Research IBM: Understand their AI initiatives and culture.
- Prepare for technical interviews: Review Python and ML fundamentals.
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