Data Scientist

Canadian Tire Corporation•Oakville, ON

5d•CA$53,000 - CA$88,000

About The Position

Canadian Tire Services Limited/Canadian Tire Bank is seeking a Data Scientist to create innovative and rewarding financial solutions for their customers. This role will involve leading machine learning projects, owning the full cycle scorecard design and development, deploying new models, and collaborating with various stakeholders to deliver effective presentations and support business objectives.

Requirements

University degree in STEM or data science.
Three plus years of professional experience focused on developing predictive scorecards and building ML models from real-world data.
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
Background in manipulating large relational databases with detailed and granular information

Nice To Haves

Postgraduate degree in mathematics, statistics, data science or similar disciplines is preferred
Work in credit risk management or the credit card industry is an asset
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

Responsibilities

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