Senior Data Scientist

FGL Sports; Oakville; On-site; CAD 110,000 - 160,000; Full time

Job summary

Canadian Tire Bank in Oakville, Ontario is seeking a Senior Data Scientist to lead the development of predictive models across the credit card customer lifecycle. You will own end-to-end model delivery, from data sourcing through validation and deployment, working with cross-functional teams to drive responsible credit decisions.

The role emphasizes analytical rigor, regulatory soundness, and business impact, with opportunities to influence consumer strategies and present complex results to

Qualifications

• University degree in Statistics, Actuarial Science or Mathematics.
• Five years or more experience with machine learning building predictive models, developing scorecards, performing statistical analysis, and segmenting customers.
• Exposure to credit risk management, credit card/banking or fraud is a plus.
• Proficient in SQL, Python and SAS programming languages.
• Experience with ML libraries: Pandas, XGBoost, scikit-learn and LightGBM.
• Familiar with FICO Analytics Workbench, SAS Enterprise Miner, Knowledge Seeker, SPSS Modeler and other software ecosystems; Databricks a plus.
• Strong analytical, mathematical, programming and problem-solving skills.
• Ability to understand large volumes of granular data and translate business needs into statistically sound solutions.
• Excellent communication of analytical results to stakeholders.

Responsibilities

• Lead machine learning projects that drive origination, credit limit and collection strategies.
• Own the full cycle scorecard design and development from data sourcing to modeling and validation.
• Deploy new models and monitor day-to-day scoring activities and handle issues.
• Monitor model performance and recommend actions for improvement.
• Perform optimization analyses and build supporting predictions.
• Create customer segmentation schemes for strategic insights.
• Collaborate with internal customers and partners to translate business needs into solutions.
• Present key design elements and model results to senior management.
• Work on related tasks to support business objectives.

Skills

Machine learning

Scorecards

SQL

Python

SAS

XGBoost

LightGBM

Pandas

Data visualization

Communication

Education

Bachelor's degree in Statistics/Actuarial Science/Mathematics

Postgraduate degree in a related discipline

Tools

SQL

Python

SAS

Pandas

XGBoost

LightGBM

Databricks

Job description

What the opportunity is

The Modeling & Segmentation Analytics Team at Canadian Tire Bank is responsible for developing and maintaining a robust suite of predictive models that support decisioning across our credit card customer lifecycle. We build risk scorecards and classification models used for acquisition, account management, and collections strategies, with a strong emphasis on analytical rigor, regulatory soundness, and business impact. As part of our continued growth, we are seeking a Senior Data Scientist who can play a key role in advancing our modeling capabilities, influencing consumer strategies, and delivering high‑quality, data-driven, machine learning models that inform responsible credit decisions. Reporting directly to the Manager of Data Modeling, you'll be working with a group of other data scientists in charge of the whole model development and monitoring process.

What you'll do

• 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 and track day‑to‑day scoring activities, addressing system or procedural issues as needed
• Monitor effectiveness of all statistical models and recommend appropriate course of action
• Perform optimization analysis and build supporting component predictions
• 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

Who you are

• A creative and courageous quick learner with the ability to navigate in an environment of change and ambiguity and help us take bold, strategic moves in a rapidly evolving and competitive marketplace
• Action‑oriented, self‑starter comfortable taking calculated risks to better serve our customers and to support business objectives
• Outcome‑focused, critical thinker with the ability to analyze and visualize, to ensure continuous improvement across our entire business Collaborative team player with excellent interpersonal skills, who builds relationships easily across various stakeholder groups to move initiatives forward

What you bring

• University degree in Statistics, Actuarial Science or Mathematics. Postgraduate degree in a related discipline is a plus
• Five years or more experience with machine learning building predictive models, developing scorecards, performing statistical analysis, and segmenting customers. Exposure to credit risk management, credit card/banking or fraud is a plus
• Solid understanding of the steps required in model development and the principles of various modeling methodologies. Experience in WOE binning and logistic regression to build scorecards is a plus
• Proficient in SQL, Python and SAS programming languages. Comfortable with ML processes like Pandas, XGBoost, scikit‑learn and LightGBM is a plus
• Familiar with FICO Analytics Workbench, SAS Enterprise Miner, Knowledge Seeker, SPSS Modeler and other software ecosystems. Experience in Databricks is a plus
• Demonstrated superior analytical, mathematical, programming and problem‑solving skills
• Ability to accurately and consistently understand and manipulate large volumes of granular and detailed data
• Proven ability to translate business needs into statistically sound solutions
• Capable of clearly communicating analytical results to business stakeholders

About Canadian Tire Bank

Established in 2003 as part of Canadian Tire Corporation, Limited (CTC), Canadian Tire Bank is a Schedule I Canadian chartered bank and a core component of CTC's integrated retail and financial services model. We offer credit cards, savings, and investment products that are closely linked to our Triangle™ Rewards ecosystem, enabling Canadians to earn value through everyday purchases across banners under CTC's umbrella, including Canadian Tire, Mark's, SportChek, Atmosphere, PartSource, Gas+, Pro Hockey Life, Hockey Experts, Sports Experts and Party City . Serving customers through approximately 1,700 retail and gasoline outlets nationwide, Canadian Tire Bank is an integral part of CTC's True North strategy, guided by our unifying goal to make life in Canada better . Since 2005, Canadian Tire Jumpstart Charities has been helping kids overcome financial and accessibility barriers to sport and recreation in an effort to provide inclusive play for all kids of all abilities. At the heart of Canadian Tire Bank is our philosophy of building "Customers for Life." We are focused on delivering customer service excellence and value‑added products through a deep understanding