Manager, Quantitative Analysis

3 weeks ago

Toronto, Canada BMO Financial Group Full time

100 King Street West Toronto Ontario,M5X 1A1

The Quantitative Analysis and Strategy (QAS) team works closely with Corporate Treasury internal Structured Market Risk, Liquidity & Funding, and Portfolio Management partners and Lines of Business partners across the bank in identifying and quantifying risks and opportunities through analytical support and statistical model development. The analysis and modeling work cover areas of mortgage, home equity, C&I and CRE loans, consumer & commercial deposits, various securities including MBS, ABS, Muni bonds, etc.

The Manager of QAS team in Corporate Treasury will be responsible for developing, enhancing, implementing and maintaining quantitative models and analytics suites using conventional econometric and machine learning techniques for the purposes of asset liability and interest rate risk management, customer analytics and 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.
- Use Machine Learning and Artificial Intelligence techniques to analyze loans and deposits accounts and customer-level data to specify models or quantitative assumptions that can help Line of Business and Treasury to better understand interest rate risk and customer behavior. Ensure that specification makes business sense.
- Write detailed documentation of the developed methodologies, including data construction, methodology specification, results, and testing.
- Put together PowerPoint presentations to present the developed methodologies to Line of Business and Corporate Treasury management to explain complex statistical techniques in simple business language.
- Communicate with model validation to ensure successful validation of the developed methodologies.
- Monitors and tracks developed and future model performance, and address any potential issues
- Construct dashboard presentation to assist business decision making and identify model performance issues in a more efficient way
- Help with routine processes such as stress testing model runs and annual model reviews.
- Assist with ad-hoc analysis requests from Line of Business partners and other Corporate Treasury teams.

**Qualifications**
- Master’s degree in a quantitative field (Statistics, Mathematics, Engineering, Economics, Mathematical Finance) and/or combination of quantitative and business degrees required, Ph.D. preferred
- 3+ years of strong hands-on computational development skills, particularly statistical and database modeling tools (SAS, R, SQL, Python, Hadoop, Access/VBA etc.), ability to adapt to various programming languages and environments.
- Strong data analysis skills, and able to deal with large data sets to extract relevant information.
- Proficiency with statistical/econometric modeling techniques
- Experience with Machine Learning and Artificial Intelligence techniques is preferred

Applies knowledge of advanced analytic algorithms and technologies (e.g. machine learning, deep learning, artificial intelligence) to deliver better predictions and/or intelligent automation that enables smarter business decisions, improved customer experience, and drives productivity. Applies strong communication and story-telling skills to summarize statistical/algorithmic findings, draw business conclusions, and present actionable insight in a way that resonates with business/groups. Drives 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.
- Acts as a trusted advisor to assigned business/group.
- Influences and negotiates to achieve business objectives.
- Recommends and implements solutions based on analysis of issues and implications for the business.
- Assists in the development of strategic plans.
- Identifies emerging issues and trends to inform decision-making.
- Understands and analyzes complex business problem, then formulates data-driven hypotheses to drive business value.
- Builds effective relationships with internal/external stakeholders and ensures alignment.
- Supports data collection, integration, and retention requirements for data.
- Develops experimental design approaches to validate findings or test hypotheses.
- Defines innovative data solutions to loosely defined business problems by leveraging pattern detection over potentially large datasets.
- Diagnoses and resolves predictive / analytical model performance issues while monitoring system performance and implementation of efficiency improvements.
- Applies innovative and best practices to advanced analytics services to ensure high quality standards.
- Sets up change control and testing processes to ensure the quality and consistency of ongoing maintenance work.
- Develops analytical solutions and makes recommendations based on

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