Data Scientist

Job Title: Data Scientist

Location: Greater Toronto Area, ON (Hyrbrid)

Estimated Duration: Fulltime

What you’ll do

• Research innovative new machine-learning tools and techniques, and assess for suitability for adoption within the business
• Build and maintain custom predictive models, including all steps for ideation to production
• Develop benchmarks and reporting to evaluate performance of new ML models
• Participate in evaluation of new 3rd-party tools and provide guidance on adoption within the company
• Create automation processes/tools to increase efficiency within division
• Perform ad-hoc analysis as requested by business partners, manger and senior leadership and communicate results
• Perform quantitative analysis on the clients portfolio and translate results into actionable recommendations
• Foster relationships with internal business partners to develop a thorough understanding of the business & ensure that Credit Risk interests are addressed in collaborative projects
• Prioritize & manage multiple work assignments in a changing business environment to ensure that projects are implemented on time & with quality

What you bring

• University degree in a quantitative discipline, Mathematics, Statistics, preferred
• Naturally curious, with an independent drive for self-learning and understanding
• Demonstrated superior analytical, mathematical and problem-solving skills.
• Proven ability to program in pertinent languages, including SAS, SQL, Python
• Proven ability to translate business needs into statistically sound solutions, and vice versa
• Big picture thinking: Ability to step back and understand impacts on a larger scale and explain complex analytical recommendations to both technical and non-technical stakeholders
• A high level of attention to detail and an ability to map business needs into solution requirements
• Strong written and oral communication skills when presenting results to business stakeholders
• Knowledge of the credit card lifecycle & credit risk management is preferred