Data Scientist
Eleks
Posted: March 6, 2026
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Quick Summary
Developing predictive models for various business needs with a strong focus on machine learning and data science.
Required Skills
Job Description
ELEKS Artificial Intelligence Office is looking for a Data Scientist in Canada.
REQUIREMENTS:
• 5+ years of experience in the data science field working with analytical and machine learning solutions
• Strong Python skills and practical experience with common data science and machine learning libraries
• Experience building predictive models and working with structured and unstructured datasets
• Hands-on experience with anomaly detection, statistical analysis, or advanced analytical techniques
• Experience developing optimization models or analytical solutions for decision support
• Degree in Data Science, Computer Science, Mathematics, Statistics, Engineering, or a related analytical field, or equivalent practical experience
• Solid understanding of data science methodologies, statistical modelling, and machine learning concepts
• Experience working with large datasets and applying analytical techniques to derive actionable insights
• Ability to communicate analytical findings clearly to both technical and non-technical stakeholders
• At least an Upper-Intermediate level of English
RESPONSIBILITIES:
• Develop and improve data-driven models to support forecasting, optimization, and business insights
• Analyze large and complex datasets to identify patterns, trends, risks, and opportunities for improvement
• Design, build, and validate machine learning models for prediction, anomaly detection, and analytical use cases
• Develop and maintain scalable data science workflows and collaborate closely with data engineers, analysts, and other stakeholders
• Translate business problems into analytical approaches and present insights and recommendations
• Support deployment of analytical models and ensure they are reliable, scalable, and maintainable in production environments
• Monitor model performance and continuously refine models based on new data and feedback
• Contribute to knowledge sharing and improvement of data science practices, tools, and methodologies within the team