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Junior Risk Analyst Jobs in Toronto, ON (NOW HIRING)

... junior analysts, and championing best practices in data science and risk modeling. You'll join an ... experienced team focused on Getting Stuff Done (#GSD), where curiosity, scientific rigor, and ...

Senior Analyst, Finance

Toronto, ON · Hybrid

CA$90K - CA$122K/yr

Work duties include research, data analysis, valuation and risk assessment across a broad range of ... Provide transaction support as a junior team member throughout financing processes. Experience ...

Functions within the team can include remediating issues identified; control and risk management ... As required, acts as an effective layer of escalation for junior or less experienced staff on ...

Junior Account Manager

Toronto, ON · On-site

CA$70K - CA$75K/yr

Bachelor's degree from an accredited college or university with major in Risk Management, Business ... Analytical and interpretive skills * Strong organizational skills * Excellent interpersonal skills

... risk, and running rebalancing and inter-store transfers to chase demand. * Own initial allocation ... junior planners, even without direct reports. What you'll bring to the team * 4-6 years of ...

Showing results 41-60

Junior Risk Analyst information

See Toronto, ON salary details

$29.1K

$93.1K

$380.8K

How much do junior risk analyst jobs pay per year?

As of Sep 4, 2026, the average yearly pay for junior risk analyst in Toronto, ON is $93,058.00, according to ZipRecruiter salary data. Most workers in this role earn between $42,945.00 and $87,322.00 per year, depending on experience, location, and employer.

What is a junior risk analyst?

A Junior Risk Analyst is an entry-level professional responsible for identifying, assessing, and mitigating potential risks within an organization. They analyze financial data, market trends, and operational processes to help senior risk analysts and management make informed decisions. Key tasks include data collection, risk modeling, report preparation, and ensuring compliance with regulatory guidelines. Strong analytical skills, attention to detail, and knowledge of risk management principles are essential for success in this role.

What are the typical responsibilities of a junior risk analyst on a day-to-day basis?

As a Junior Risk Analyst, your daily tasks often include gathering and analyzing data related to market, credit, or operational risks, preparing risk reports, and assisting with the development of risk models. You may also support more senior analysts with research projects, help monitor compliance with risk policies, and participate in meetings to discuss findings and recommendations. Collaboration with other departments, such as finance, compliance, and operations, is common to ensure all relevant data is considered. This role provides hands-on experience in risk assessment processes and working as part of a broader risk management team, making it a great opportunity to learn and grow in the field.

What are the key skills and qualifications needed to thrive in the junior risk analyst position, and why are they important?

To thrive as a Junior Risk Analyst, you need strong analytical abilities, attention to detail, and a degree in finance, economics, mathematics, or a related field. Familiarity with risk management software, Excel, data analysis tools, and an understanding of regulatory frameworks such as Basel or SOX are beneficial, and certifications like FRM or CFA are advantageous. Effective communication, critical thinking, and a collaborative mindset are key soft skills for excelling in this role. These competencies enable you to accurately assess risks, contribute valuable insights, and work seamlessly within interdisciplinary teams to support organizational decision-making.

How much do risk analysts get paid?

Risk analysts typically earn a median annual salary of around $70,000 to $90,000, depending on experience, location, and industry. Entry-level positions may start lower, while experienced analysts or those with specialized skills can earn over $100,000 annually.

How to become a junior risk analyst with no experience?

To become a junior risk analyst with no experience, focus on gaining relevant skills such as data analysis, Excel, and understanding risk management concepts through online courses or certifications. Internships or entry-level positions in finance or data analysis can provide practical experience, and a bachelor's degree in finance, economics, or a related field is often required.

What are the most commonly searched types of Risk Analyst jobs in Toronto, ON?

The most popular types of Risk Analyst jobs in Toronto, ON are:

What are popular job titles related to Junior Risk Analyst jobs in Toronto, ON?

For Junior Risk Analyst jobs in Toronto, ON, the most frequently searched job titles are:

What job categories do people searching Junior Risk Analyst jobs in Toronto, ON look for?

The top searched job categories for Junior Risk Analyst jobs in Toronto, ON are:

What cities near Toronto, ON are hiring for Junior Risk Analyst jobs?

Cities near Toronto, ON with the most Junior Risk Analyst job openings:

Infographic showing various Junior Risk Analyst job openings in Toronto, ON as of August 2026, with employment types broken down into 1% As Needed, 89% Full Time, 8% Part Time, and 2% Contract. Highlights an 86% Physical, 6% Hybrid, and 8% Remote job distribution, with an average salary of $93,058 per year, or $44.7 per hour.

Data Science Manager, Risk

Fig

Toronto, ON

Full-time

Medical, Dental, Vision, Retirement

Posted 29 days ago


Key responsibilities

  • Build, enhance, and deploy machine learning models for credit risk applications.

  • Partner with model validation to ensure robust model governance through documentation, performance monitoring, and diagnostics.

  • Translate analytical solutions into scalable production workflows and automate credit decisioning.


Job description

About Fig

Fig is an award-winning, high-growth Canadian FinTech modernizing the world of consumer credit. We provide simple, accessible and fully digital personal loans, removing the complexity and delays of traditional lending to better serve Canadians.

Since launching in 2023, Fig has quickly built a strong reputation for innovation and customer trust. We have been named Consumer Lender of the Year by the Canadian Lenders Association and FinTech Startup of the Year by the FinTech Breakthrough Awards, and we are consistently recognized among Canada's Best Workplaces. Our commitment to customers is reflected in our 4.8 out of 5 Trustpilot rating.

Backed by Fairstone Bank of Canada and Ontario Teachers' Pension Plan, Fig combines deep lending expertise with the agility of a startup. This foundation allows us to effectively meet the evolving credit needs of Canadians across a wide range of financial backgrounds. 

The Role: Credit Risk Expert & Strategic Builder

We are looking for a hands-on, data-obsessed Data Science Manager, Risk to build and operationalize the models, data pipelines, and analytical frameworks that power our lending decisions. Reporting to the Director of Credit Risk, you will play a key role in advancing our credit risk capabilities through machine learning, data engineering, model governance, and data-driven experimentation. While this role does not include people management responsibilities in the short term, you will provide technical leadership by driving cross-functional initiatives, mentoring junior analysts, and championing best practices in data science and risk modeling.

You'll join an experienced team focused on Getting Stuff Done (#GSD), where curiosity, scientific rigor, and continuous innovation drive every decision. You'll work across the full model lifecycle from developing and deploying models to monitoring, governing, and continuously improving their performance. You should be comfortable navigating ambiguity, solving complex analytical problems, and translating insights into scalable, production-ready solutions.

This is an exciting opportunity to work across multiple data science disciplines, including credit risk model development, alternative labeling strategies, reject inference, model validation and quality assurance, feature engineering, model monitoring, production decisioning, and credit risk data engineering. You'll design robust data pipelines, improve model performance and governance, automate analytical workflows, and partner closely with Credit Strategy, Product, Finance, Growth and Engineering to deliver scalable, data-driven lending solutions. This is a newly created role, which means you'll have the opportunity to help shape the mandate, build core processes, and make a visible impact as Fig continues to grow.

Culture matters deeply to us. You'll have the support of experienced colleagues across the organization who are passionate about solving challenging problems together. We're looking for someone who combines strong technical expertise with curiosity, collaborates effectively across teams, and thrives in an environment that values transparency, accountability, and continuous improvement.

What You'll Do
  • Develop Next-Generation Credit Models: Build, enhance, and deploy machine learning models for underwriting, reject inference, alternative labeling, and other credit risk applications.

  • Drive Model Governance & Quality: Partner with model validation to ensure robust model governance through comprehensive documentation, performance monitoring, stability analysis, diagnostics, and ongoing model enhancements.

  • Advance Credit Strategy: Partner with the Credit Risk team to evaluate underwriting policies, optimize risk segmentation, and translate model insights into data-driven credit strategies.

  • Enable Scalable Credit Analytics: Develop analytical datasets, reusable feature frameworks, and scalable workflows that accelerate model development, portfolio monitoring, and strategic decision-making.

  • Drive Statistical Experimentation: Design and evaluate statistically rigorous experiments to assess new models, features, and credit strategies, using data to quantify business impact and optimize decision-making.

  • Productionize Decisioning: Translate analytical solutions into scalable production workflows, partnering with Engineering to automate credit decisioning and improve operational efficiency.

  • Build AI-Powered Solutions: Develop and deploy AI-powered solutions across credit risk and fraud to enhance decision-making, strengthen fraud detection, and improve operational efficiency.

  • Collaborate Across Teams: Partner closely with Credit Strategy, Product, Growth, Finance, Engineering, and Data teams to deliver high-quality, data-driven solutions that balance portfolio growth, risk, and customer experience.

What You'll Bring
  • Subject Matter Experience: 4 or more years of experience in Credit Risk management, modeling and/or related data analysis in a financial services, FinTech, lending and/or technology company.

  • Technical Mastery: Strong proficiency in Python and SQL is required.

  • Analytical Depth: Working knowledge of regression analysis, decision trees, loss forecasting, and statistical design of experiments.

  • Exceptional Communication Skills: The ability to translate complex data into clear, professional narratives for Senior Management.

  • Startup DNA: You thrive in fast-paced environments with limited structure and have a shared sense of purpose to "Get Stuff Done" (#GSD).

Why Fig?
  • Make Your Mark: This is a rare chance to help directly steward a high-impact FinTech in Canada at an exciting stage of its growth and maturity.

  • The Culture: Work in a team that values impact, accountability, curiosity, and building strong, collaborative relationships.

  • Hybrid Work Environment: Balance of remote and in-office (currently one day a week in Toronto), without sacrificing the high-energy collaboration.

  • Competitive compensation ($95,000 - $120,000 base + bonus).

  • Retirement savings program with employer matching.

  • Comprehensive medical, dental, and vision group insurance, as well as health and wellness spending accounts.

  • Generous time off to help you recharge.

  • Parental top-up to support your growing family.

  • Continuing education stipend to support your professional development.

Our commitment to diversity, equity and inclusion

We are an equal opportunity employer and are committed to diversity at our company. We do not discriminate on the basis of race, religion, culture, sexual orientation, gender identity and physical ability.

Diversity of backgrounds, perspectives, and experience is fundamental to our business. We believe in fostering an environment where team members of all backgrounds can feel comfortable bringing their whole selves to work every day. We aim to ensure all of our employees work in an environment that makes them feel valued, heard, and supported while they strive towards career pursuits and their personal and professional growth.

We are committed to providing accommodations for all candidates that require them and in all aspects of the recruitment, selection, and/or assessment process. If you are selected to participate in any part of the selection and/or assessment process, please inform us of any accommodation(s) that you may require.

AI Disclosure

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

We're flattered that you'd like to join our team, but only applicants selected to proceed in the hiring process will be contacted.

$95,000 - $120,000 a year
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
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