Data Scientist, Risk Analytics & IFRS9 Modeling

Financeit; Toronto; Hybrid; CAD 75,000 - 100,000; Full time

Benefits offered by this job

Hybrid workplace

Medical, dental and vision coverage

RRSP Matching

In-office wellness (massage, méditaion

Virtual events

Career learning and development

Job summary

Financeit is seeking a Data Scientist, Risk Analytics & Modeling, to develop and deliver risk machine learning and statistical models for credit decisioning, portfolio management, and risk measurement. You will help build IFRS 9 models and other predictive risk solutions while automating processes and turning data into actionable insights for stakeholders.

You will work under the Director - Risk Analytics, Data Science & Reporting and collaborate with cross-functional teams to operationalize

Qualifications

• University degree in Engineering, Math, Computer Science, Applied Math or Applied Sciences, Finance, or another quantitative discipline
• 0-3 years of full-time and/or internship/PEY experience in analytics, data science, risk management, finance, or a related quantitative field
• Foundational experience with Python, SQL, Excel, or similar analytical tools; experience building models, working with data, or automating processes is a strong asset
• Exposure to machine learning, statistical modeling, credit risk, IFRS 9, behavioural modeling, or financial modeling would be a strong asset
• Strong pragmatic quantitative thinking, judgment, communication (verbal, visual, and written), with a demonstrated ability to break down complex problems and explain your work
• Curious and eager to learn, with the ability to dig into data, question assumptions, and develop an understanding of how models behave in the real world
• Highly organized and driven, with the ability to manage competing priorities while meeting deadlines
• A balanced sense of confidence and humility, with the ability to thrive in a collaborative environment and bring energy and enthusiasm to team culture
• Capable of having fun while doing all of the above; we’re serious about this

Responsibilities

• Build, validate, and refine sophisticated risk machine learning and statistical models across consumer credit, fraud, portfolio risk, and borrower behaviour
• Develop and enhance IFRS 9 models, including expected credit loss, probability of default, loss given default, exposure at default, and related risk forecasting and segmentation methodologies
• Build behavioural and predictive models that leverage customer, transaction, portfolio, and macroeconomic data to better understand and predict borrower behaviour and credit outcomes
• Go beyond the surface level to build sophisticated yet explainable models that connect data to real-world events, customer attitudes and behaviours to deliver insights and inform high-value business decisions
• Translate complex analytical problems into scalable modelling solutions, while balancing statistical rigour, interpretability, business impact, and practical implementation
• Identifying high quality, well-managed data sources and opportunities to apply automation, data pipelines, machine learning, and AI to your work
• Participate in strategic projects and partner with cross-functional teams to support resourcing for modelling and reporting
• Document all models, methodologies, policies, strategies, data sets, and tools (using tools like Confluence) to ensure clarity and accurate internal transfer of knowledge
• Stay curious and experiment with new modelling techniques, analytical approaches, automation tools, and emerging technologies to continuously improve how we solve risk problems

Skills

Data science

Statistical modeling

Data engineering

Automation

Explainable predictions

Education

University degree in Engineering, Math, CS, Applied Math or Quantitative discipline

Tools

Python

SQL

Excel

Job description

Financeit is seeking a Data Scientist, Risk Analytics & Modeling, to develop and deliver risk machine learning and statistical models for credit decisioning, portfolio management, and risk measurement. You will help build IFRS 9 models and other predictive risk solutions while automating processes and turning data into actionable insights for stakeholders.

You will work under the Director - Risk Analytics, Data Science & Reporting and collaborate with cross-functional teams to operationalize