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# Data Scientist

- **Company:** Canadian Tire Corporation, Limited
- **Location:** United States (Remote available)
- **Experience:** Experienced
- **Salary:** $53,000.0 - $88,000.0
- **Contract:** Permanent contract
- **Skills:** Amazon Web Services, Data Analysis, Microsoft Azure, Cloud Database, Relational Databases, Python (Programming Language), Machine Learning, RapidMiner, Standard Sql, SAS (Software), Pandas, Scikit Learn, Xgboost, Software Library, Databricks
- **Published:** September 25, 2026
- **Apply:** https://arc.dev/remote-jobs/j/redirect/pmvyct6yj7

## About the Role

* University degree in STEM or data science. Postgraduate degree in mathematics, statistics, data science or similar disciplines is preferred
 * Three plus years of professional experience focused on developing predictive scorecards and building ML models from real-world data. Work in credit risk management or the credit card industry is an asset
 * Solid understanding of machine learning steps and modeling metrics is a must
 * Proficient in SQL, Python and, ideally, SAS programming language
 * Experience with machine learning libraries like Pandas, XGBoost, scikit-learn, LightGBM or other similar ecosystems
 * Hands-on exposure to modeling platforms like Enterprise Miner, Analytics Workbench or SPSS Modeler is a plus
 * Comfortable with cloud-based data structures and tools like Azure, AWS and Databricks is a plus
 * Background in manipulating large relational databases with detailed and granular information

## Description

* Lead machine learning projects that drive origination, credit limit and collection strategies including managing delivery timelines and coordinating team resources
 * Own the full cycle scorecard design and development from initial planning and data sourcing to data modeling and validation
 * Deploy new models, implement updates, track data transfers, oversee scoring activities, and manage reports, addressing system or procedural issues as they arise
 * Regularly review and document the predictive effectiveness of various statistical models and recommend the appropriate course of action
 * Create customer segmentation schemes that provide strategy teams with key customer insights
 * Collaborate closely with internal customers, retail-side partners and subject matter experts to understand data, interpret results, translate business needs and synthesize solutions
 * Deliver effective presentations of key design elements and model build results to senior management
 * Work on related tasks and ad hoc activities to support business objectives