Senior Analyst, Quantitative Analysis at Bank of Montreal

Toronto, Ontario, Canada -

Full Time

Start Date

Immediate

Expiry Date

09 Feb, 26

Salary

124200.0

Posted On

11 Nov, 25

Experience

0 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Statistical Analysis, Data Mining, Data Cleansing, Machine Learning, Deep Learning, Programming, SQL, Python, R, SAS, SPSS, Matlab, Data Visualization, Cloud Technologies, Distributed Computing, Analytical Skills

Industry

Financial Services

Description

Application Deadline: 11/12/2025 Address: 100 King Street West Job Family Group: Data Analytics & Reporting The Senior Analyst, Quantitative Analysis, Strategy and Insights in Corporate Treasury is ideal for candidate who wants to work on developing, enhancing, implementing and maintaining quantitative models and analytics suites. They would do so by using conventional econometric and machine learning techniques, for the purposes of asset liability, liquidity, and interest rate risk management, customer analytics, profitability, and stress testing under various macro-economic scenarios. This involves analyzing large account-level and transaction-level data, articulating the problem statement, and specifying the most appropriate quantitative solution. The successful candidate is someone who can: Effectively apply knowledge of advanced analytic algorithms and modeling techniques (e.g. large data processing, statistical modeling, machine learning) to deliver better predictions and/or intelligent automation that enables smarter business decisions, improved customer experience, and drives productivity. Confidently and clearly communicate and summarize statistical/algorithmic findings. Draw business conclusions and present actionable insight in a way that resonates with business/groups (i.e., story-telling skills) Drive innovation through the development of Data & AI products that can be leveraged across the organization and establishes best practices in in alignment with Data & AI governance frameworks of BMO. Responsibilities: Applies scripting / programming skills to assemble various types of source data (unstructured, semi-structured, and structured) into well-prepared datasets with multiple levels of granularities (e.g., demographics, customers, products, transactions). Develops agreed analytical solution by applying suitable statistical & machine learning techniques (e.g., A/B testing, prototype solutions, mathematical models, algorithms, machine learning, deep learning, artificial intelligence) to test, verify, refine hypotheses. Summarizes statistical findings and draws conclusions, presents actionable business recommendations. Presents findings & recommendations in a simple, clear way to drive action. Supports development of tools and delivers training for data analytics and AI. Uses the appropriate algorithms to discover patterns. Performs experimental design approaches to validate finding or test hypotheses Provides timely ad-hoc analytical support to business and other key stakeholders Automates and enhances processes to generate scheduled reports — detailing accurate balance sheet position and actionable analytical insights to stakeholders in an efficient and timely manner Works with various data owners to discover and select available data from internal sources and external vendors (e.g. lending system, payment system, external credit rating system, and alternative data) to fulfill analytical needs. Documents data flow, systems and processes in data collection to improve efficiency and apply use cases. Works with stakeholders to identify the business requirements, understand distinct problems and expected outcomes. Develops analytical solutions and makes recommendations based on an understanding of the business strategy and stakeholder needs. Builds effective relationships with internal/external stakeholders and ensures alignment. Provides advice and guidance to assigned business/group on implementation of analytical solutions. Supports development and execution of strategic initiatives in collaboration with internal and external stakeholders. Leads/participates in the design, implementation and management of core business/group processes. Broader work or accountabilities may be assigned as needed. Qualifications: Typically between 1-2 years of relevant experience and graduate-level degree in related field of study or an equivalent combination of education and experience. Experience in statistical analysis, data mining, and data cleansing / transformation. Knowledge of visualization techniques and concepts (e.g, Power BI, SpotFire). Experience with programming languages (e.g. SQL, Python, R, SAS, SPSS, Matlab) and machine learning /deep learning algorithms/packages (e.g. XGBoost, H2O, SparkML). Knowledge of distributed computing and/or distributed databases. Experience with distributed computing language (e.g. Hive / Hadoop/ Spark) & cloud technologies (e.g. AWS Sagemaker, AzureML). Exercises judgment to identify, diagnose, and solve problems within given rules. Works independently on a range of complex tasks, which may include unique situations. Data driven decision making - In-depth. Verbal & written communication skills - In-depth. Collaboration & team skills - In-depth. Analytical and problem solving skills - In-depth. Influence skills - In-depth. Technical proficiency gained through education and/or business experience. Salary: $67,200.00 - $124,200.00 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.

Responsibilities

The Senior Analyst will develop, enhance, implement, and maintain quantitative models and analytics suites for asset liability, liquidity, and interest rate risk management. They will analyze large datasets and present actionable insights to drive business decisions.