Manager, Lending Strategy Reporting & Insights at BMO — NeverHard
Manager, Lending Strategy Reporting & Insights at BMO in Toronto, Ontario. Skills: Credit Risk, Data Analysis, Data Transformation, Python, Reporting. Apply on NeverHard.
Company
BMO
Location
Toronto, Ontario
Type
part_time
Remote: Yes
Required skills:
Credit Risk
Data Analysis
Data Transformation
Python
Reporting
SQL
Application Deadline:
07/26/2026
Address:
33 Dundas Street West
Job Family Group:
Audit, Risk & Compliance
#FutureofRetailLending
Join a pioneering team shaping the future of Canadian Retail Credit Strategies.
We're building next-generation, end-to-end credit solutions that span the entire lifecycle-from acquisition and account management to collections-anchored in a holistic
Lending Decision Strategy
and aligned with
Canadian Personal & Business Banking (P&BB)
priorities.
Our approach combines cutting-edge decisioning software, advanced decision trees, and innovative credit models to deliver smarter, faster, and more customer-centric outcomes. This is your opportunity to influence credit cycles using modern modeling techniques and best-in-class decisioning applications, all within a high-performance, customer-focused environment.
If you're passionate about leveraging data, technology, and strategy to transform lending decisions and drive meaningful impact across Canadian P&BB, this is the team for you
The
Manager, Lending Strategy Reporting & Insights
transforms data into decision-ready insight across the
customer credit lifecycle
-from acquisition and underwriting through account management, fraud, and collections-across Consumer and Business Banking credit products as well as an accountability for Credit Risk Campaign Design & Measurement
1)
Analytics Engineering & Data Transformation
Use
Python
and
SQL
to transform data into reusable, analytics-ready datasets.
Understand, execute, and maintain existing
SAS scripts and reporting processes
.
Analyze business logic embedded in SAS programs and ensure continuity and accuracy of outputs.
Translate SAS-based logic into
Python-based workflows
where appropriate.
Design and enhance monitoring frameworks including automated alerts, validation controls, and data-driven indicators to ensure accuracy and reliability.
Standardize and optimize data transformations for scalability, maintainability, and reuse.
Ensure datasets are structured and optimized for efficient consumption in
Power BI reporting and dashboards
.
2) Governance, Risk Alignment & Controls
Use
Git/GitHub
for version control, collaboration, and structured code management.
Ensure proper documentation, reproducibility, and auditability of analytics and reporting processes.
Apply best practices for code quality, modularity, and reusability across Python, SAS, and Power BI assets.
Ensure alignment with enterprise data governance, risk appetite, and regulatory expectations.
3)Credit Lifecycle Analytics & Decision Support
Develop a connected
lifecycle view
that links acquisition risk profiles, account-management actions (e.g., limit management, pricing, treatments), fraud signals, payment performance, and collections outcomes.
Partner with
Credit Risk, Product, Marketing, Fraud, and Collections
to translate insights into
strategy adjustments, treatment design, champion/challenger tests
, or policy changes.
Stand up monitoring for
new products, policy changes, and strategy deployments
to enable early feedback loops and rapid course-correction.
4)
Executive Reporting & Visualization (Power BI)
Design and develop Power BI dashboards
and semantic models (Power Query, DAX) to deliver scalable, executive-ready reporting and insights.
Optimize Power BI data models and report performance
for usability, scalability, and self-service analytics.
Distill complex analysis into
concise narratives
with a clear POV and next-best actions; quantify expected impact and measurement plans.
Must-Have
3+ years of progressive experience in Credit Risk, Portfolio Management, Lending, or advanced analytics across consumer and/or business credit portfolios.
Hands-on experience with:
Python
(data transformation, automation)
Git/GitHub
(version control, collaboration workflows)
SAS
(ability to read, execute, and modify existing scripts)
Power BI
(Power Query, DAX, data modeling, and dashboard development)
Demonstrated ability to
translate complex data into strategic insights
and influence stakeholders with
concise, decision-ready narratives
.
Hands-on expertise building
monitoring frameworks
,
early-warning indicators
, behavioral segmentation, and performance measurement/back-testing.
Strong stakeholder management skills, with the ability to communicate effectively, align expectations, and proactively identify and flag risks or gaps early rather than at delivery.
Strong business acumen connecting
customer behavior, macro factors, operational signals,
and
portfolio outcomes
; comfortable with trade-off framing.
Excellent communication skills-able to brief senior audiences succinctly and coach junior analysts on
storytelling with data
.
Nice-to-Have
Experience with
credit decisioning strategies
(e.g., limit management, pricing, treatment orchestration) and experimentation (A/B, champion/challenger).
Familiarity with
model governance/model risk
concepts and stress testing; experience integrating model outputs into monitoring and strategies.
Knowledge of
collections operations, fraud operations
, and hardship programs; exposure to
macroeconomic scenario analysis
.
Degree in a quantitative field (e.g., Statistics, Economics, Finance, Data Science);
graduate degree
an asset.
Salary
:
$69,000.00 - $129,000.00
Pay Type:
Salaried
The above represents BMO Financial Group's pay range and type.
Salaries will vary based on factors such as location, skills, experience, education, and qualifications for the role, and may include a commission structure. Salaries for part-time roles will be pro-rated based on number of hours regularly worked. For commission roles, the salary listed above represents BMO Financial Group's expected target for the first year in this position.
BMO Financial Group's total compensation package will vary based on the pay type of the position and may include performance-based incentives, discretionary bonuses, as well as other perks and rewards. BMO also offers health insurance, tuition reimbursement, accident and life insurance, and retirement savings plans. To view more details of our benefits, please visit: https://jobs.bmo.com/global/en/Total-Rewards
About Us
At BMO we are driven by a shared Purpose: Boldly Grow the Good in business and life. It calls on us to create lasting, positive change for our customers, our communities and our people. By working together, innovating and pushing boundaries, we transform lives and businesses, and power economic growth around the world.
As a member of the BMO team you are valued, respected and heard, and you have more ways to grow and make an impact. We strive to help you make an impact from day one - for yourself and our customers. We'll support you with the tools and resources you need to reach new milestones, as you help our customers reach theirs. From in-depth training and coaching, to manager support and network-building opportunities, we'll help you gain valuable experience, and broaden your skillset.
To find out more visit us at https://jobs.bmo.com/ca/en .
BMO is committed to an inclusive, equitable and accessible workplace. By learning from each other's differences, we gain strength through our people and our perspectives. Accommodations are available on request for candidates taking part in all aspects of the selection process. To request accommodation, please contact your recruiter.
Note to Recruiters: BMO does not accept unsolicited resumes from any source other than directly from a candidate. Any unsolicited resumes sent to BMO, directly or indirectly, will be considered BMO property. BMO will not pay a fee for any placement resulting from the receipt of an unsolicited resume. A recruiting agency must first have a valid, written and fully executed agency agreement contract for service to submit resumes.