Manager Stress Testing Analytics

100 King Street West Toronto Ontario,M5X 1A1

Seeking a Manager, Stress Testing Analytics to join our Enterprise-Wide Stress Testing (EWST) team. In this role, you will analyze complex retail and wholesale portfolios, generate actionable insights, and produce impactful reports that guide senior leadership through a dynamic economic landscape.

What You’ll Do
- Support enterprise and adhoc stress testing activities for credit portfolios, ensuring accuracy, clarity, and relevance.
- Produce and present portfolio-level deep dives, uncovering key drivers of portfolio performance and variance across different exercises, analyze trends, early warnings.
- Partner with peers and stakeholder to interpret results, highlight emerging risks by employing statistical analysis and improve existing processes.
- Manage large datasets and advanced analytics to assess credit risk measures such as PCL, RWA, and risk ratings.

What You Bring
- 2-3 years of stress testing or risk reporting experience, ideally in a banking or financial services environment.
- Strong credit risk knowledge across retail products and wholesale portfolios.
- Hands-on experience with Python and SQL (PySpark a plus).
- Comfort working with big data and visualization tools (Power BI preferred).
- Knowledge of cloud-based analytics environments is an asset.
- A Master’s degree in Finance or related discipline.

This role based in Toronto (3-4 days in office)

If you’re looking for your next dream job, consider this one in BMO’s Enterprise Risk Group where every colleague helps protect and grow the bank by providing independent review and oversight of enterprise-wide risks, working together to maintain a risk management framework and fostering a strong risk culture. #ERPMDreamJobs

Uses advanced analytical algorithms and technologies (e.g. machine learning, deep learning, artificial intelligence) to mine and analyze large sets of structured and unstructured data to obtain insights. Designs and constructs new processes for modeling data. Develops predictive models and leverages big data technology to design solutions that deliver smarter business decisions, improve customer experience, and drive productivity. Collaborates with other data and analytics professionals and teams to optimize, refine and scale analysis into mature analytics solutions.
- Plays an active role in the futuristic display of data, and advancement of innovative data strategies to understand consumer trends and address business problems.
- Uses data mining and extracting usable data from valuable data sources to assess feasibility of AI/ML solutions for improved processing and usage of organization data.
- Conducts large-scale analysis of information to discover patterns and trends by combining different modules and algorithms.
- Uses analysis to provide recommendations and advice for business leaders to maintain to maintain market competitiveness.
- Develops prediction systems and machine learning algorithms. Investigates additional technologies and tools for developing innovative data solutions for business stakeholders.
- Collaborate together with the product team and partners to understand and provide data-driven decision making, business planning and future roadmap.
- Fosters a culture aligned to BMO purpose, values and strategy and role models BMO values and behaviours in all that they do.
- Ensures alignment between values and behaviour that fosters diversity and inclusion.
- Regularly connects work to BMO’s purpose, sets inspirational goals, defines clear expected outcomes, and ensures clear accountability for follow through.
- Builds interdependent teams that collaborate across functional and operating groups to create the highest value for all stakeholders.
- Attracts, retains, and enables the career development of top talent.
- Improves team performance, recognizes and rewards performance, coaches employees, supports their development, and manages poor performance.
- Focus is primarily on business/group within BMO; may have broader, enterprise-wide focus.
- Provides specialized consulting, analytical and technical support.
- Exercises judgment to identify, diagnose, and solve problems within given rules.
- Works independently and regularly handles non-routine situations.
- Broader work or accountabilities may be assigned as needed.

**Qualifications**:
Intermediate level of proficiency:

- Mathematics, statistics & operations research.
- Deep learning.
- Machine learning.
- Trust, bias and ethics.
- Creative thinking.
- Critical thinking.

Advanced level of proficiency:

- Big data.
- Data visualization.
- Computational thinking and programming.
- Data wrangling.
- Data preprocessing.
- Creative reasoning.
- Verbal & written communication skills.
- Collaboration & team skills.
- Analytical and problem solving skills.
- Influence skills.
- Data driven decision making.
- Typically between 5 - 7 years of relevant experience and post-secondary degree in related field of study or