Data Science Student

Responsibilities Gain proficiency in exploratory data analysis, perform it, and present insights.  Prepare data sets for visualization and machine learning modeling.  Train machine learning systems using data annotation and benchmarking techniques.  Help your colleagues assess AI/ML model performance and propose paths for potential improvement.  Prepare data visualizations using industry-leading tools to summarize results for stakeholders.  Document your results - tell the story of the work, the successes, and the lessons-learned for posterity.  Keep an open mind, in order to utilize your unique skills and your determination when other opportunities arise.      This position has a twist . Contingent on successful early work, the team member will have a chance to build their portfolio through a capstone project. For the final two months, a portion of their time will be focused on a design-focused initiative, of value to PCL, of their choosing. You'll be supported while you:  Develop a proposal  Engage with the right people to inform your work  Build your prototype or visualization  Assess and present the results  Qualifications Currently enrolled in a postsecondary program  You should be an outstanding bachelor's or mathematics student in engineering, computing, or mathematical sciences. Alternatively, you could be pursuing an MSc in a quantitative field. If your field of study differs, apply: we’d like to hear why you'll be a good fit regardless.  Analytical skills – ability to quickly analyze data to identify and visualize key insights – as evidenced by coursework, projects, or research requiring the analysis of large datasets.  Coursework in statistics. Applied statistics and probability are the focus of the position: if you can converse about regression models, and clustering approaches, you'll be fine.  Prior exposure to a statistical or scientific programming environment is helpful. If you don't have it, you'll become familiar while you're with us.  We have a bias for open source tech, and work with the Python scientific stack, R, PowerBI, and various data pipeline tools.  Excellent oral and written communication skills will help. You'll work with both experts in the field and business staff, so you’ll find it important to be able to communicate appropriately with both as needed.    Next Step:  Please note that candidates who have been selected to move forward to the next stage of the recruitment process will receive an email to complete a short online video interview.