Introduction A career in IBM Consulting is built on long-term client relationships and close collaboration worldwide. You’ll work with leading companies across industries, helping them shape their hybrid cloud and AI journeys. With support from our strategic partners, robust IBM technology, and Red Hat, you’ll have the tools to drive meaningful change and accelerate client impact.

At IBM Consulting, curiosity fuels success. You’ll be encouraged to challenge the norm, explore new ideas, and create cutting-edge solutions that deliver real results. Our culture of growth and empathy focuses on your long-term career development while valuing your unique skills and experiences.

Your Role And Responsibilities

As a Data Engineer with Advanced Analytics expertise, you will specialize in formulating mathematical approaches to solve complex business problems and utilize predictive analytics tools to draw conclusions and present findings. You will design, build, and manage solutions that involve preparing data, performing statistical analysis, and deploying analysis results.

Your Primary Responsibilities Will Include

- Formulate Mathematical Approaches: Learn to develop mathematical optimization, discrete-event simulation, and rules programming techniques to solve complex business problems.

- Prepare and Analyze Data: Assist with gathering and preparing data, performing statistical analysis, data collection, data mining, and text mining to support advanced analytics projects.

- Deploy Analysis Results:



Participate in deploying analysis results and presenting findings using predictive analytics tools like SPSS.

- Apply Data Engineering Principles: Explore data engineering principles and learn to apply them to advanced analytics projects under guidance.

- Support Solution Development: Engage in designing, building, and managing solutions that involve data preparation, analysis, and deployment.

Required Technical And Professional Expertise

- Basic Understanding of Mathematical Optimization: Exposure to mathematical approaches, including optimization, discrete-event simulation, and rules programming, to solve complex business problems.

- Familiarity with Predictive Analytics Tools: Interest in utilizing predictive analytics tools like SPSS to draw conclusions and present findings.

- Data Preparation and Analysis Skills: Basic understanding of data preparation, statistical analysis, data collection, data mining, and text mining concepts.

- Foundational Knowledge of Data Engineering: Curiosity about data engineering principles and their application to advanced analytics projects.

- Exposure to Solution Development: Participation in designing, building, and managing solutions involving data preparation, analysis, and deployment.

Preferred Technical And Professional Experience

- Predictive Analytics Tools: Interest in utilizing tools like SPSS for data analysis and presentation.

- Data Mining Techniques: Basic understanding of data mining and text mining concepts to support advanced analytics projects.

- Statistical Analysis Methods: Familiarity with statistical analysis and data collection methods for data-driven insights.

📌 Consultant Intern Return (Toronto)
🏢 IBM
📍 Toronto