Manager, Credit Risk Modeling - Decision Science

Manager, Credit Risk Modeling - Decision ScienceLocation: Toronto, ON, CANTime Type: Full timePosted on: Posted 2 Days AgoJob Requisition ID: R240023775Application Deadline: 11/28/2024Address: 33 Dundas Street WestJob Family Group: Data Analytics & ReportingRole Summary/PurposeThe role is responsible for supporting various data science projects including development and maintenance of the origination, portfolio risk management and collection models/strategies for Canadian Personal & Business Banking (P&BB) small business portfolios. The individual will assist senior manager in developing various machine learning solutions for risk management and monitoring model performance.Applies mathematical and statistical methods to financial and risk management problems (e.g., internal controls; enterprise-wide stress testing and scenario analysis; capital modelling; valuations). Through quantitative analytical modelling, identifies important factors to consider for financial disaster and recovery plans. Conducts research and creates tools that use data to develop scenario-based planning and implements complex mathematical models to help the business make better financial decisions (e.g., investments, pricing, etc.), drive innovation and minimize the impact of uncertainty.Develops pricing and quantitative risk models for an assigned portfolio e.g., fixed income, corporate credit, and loans.Support the development and maintenance of machine learning statistical and/or other scoring and forecasting models and tools by assisting with data engineering and data science tasks.Work with risk and lines of business teams to develop analytic solutions, ad-hoc analysis, and modeling to drive new initiatives, improve business processes, and deliver value using data-driven decisions.Monitors risk in strategies and portfolios alongside project managers or functional leads.Design, develop and maintain code used for data engineering and data science tasks in order to prepare, manipulate and analyze large internal and external datasets using SAS, R, Python, or SQL.Support the delivery and enhancement of regularly scheduled (monthly, quarterly) reporting packages for models and/or credit risk strategic initiatives.Conducts research and develops tools that use data to make better financial decisions; such as: investments, pricing, etc.Applies knowledge of risk assessment and controls along with extensive understanding of industry compliance standards and regulations.Identifies ways of mitigating potential risks; recommends and implements solutions based on analysis of issues and implications for the business.Documents data flow, systems, and processes to improve the design, implementation, and management of business/group processes.Conducts quantitative research in risks across strategies and portfolios.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:Degree in Statistics, Mathematics, Actuarial Science, Engineering, Operations Research, or another highly quantitative field with a track record of academic excellence.At least 2 years’ experience with developing data science and data engineering solutions.Understanding of credit risk concepts is an asset.Knowledge of various statistical software skills including SAS, R, Python, etc.Desired Characteristics:Advanced programming skills; proficiency with programming languages such as R, SAS, Python, or SQL; and a high level of familiarity with Microsoft Office tools.Strong project management skills with the ability to manage multiple assignments effectively.Understanding of risk management concepts including Probability of Default (PD), Exposure at Default (EAD) and Loss Given Default (LGD), etc.Experience developing data science models and solutions.Experience working with big data.Foundational level of proficiency:Regulatory capital and stress testing.Compliance and regulation.Machine learning.Learning Agility.Systems Thinking.Intermediate level of proficiency:Model risk management.Data visualization.Data wrangling.Data preprocessing.Critical thinking.Driving Results.Verbal & written communication skills.Collaboration & team skills.Analytical and problem solving skills.Data driven decision making.Advanced level of proficiency:Quantitative financial modeling.Computational thinking and programming.Typically between 5 - 7 years of relevant experience and post-secondary degree in related field of study or an equivalent combination of education and experience.Deep knowledge and technical proficiency gained through extensive education and business experience.Salary: $81,600.00 - $151,200.00Pay Type: SalariedThe above represents BMO Financial Group’s pay range and type.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.We’re here to helpAt 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.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. #J-18808-Ljbffr