Manager, Credit Risk Modeling - Decision Science (BB-7E873)
Found in: Talent CA
Description:Address: 55 Bloor 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. The individual will assist senior manager in developing various machine learning solutions for risk management and monitoring model performance.Essential ResponsibilitiesSupport 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 tasksWork 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. This includes but is not limited to the development of data science and business intelligence solutions across consumer and small business products.Provide analytical solutions involving descriptive, predictive, and prescriptive analysis through the retail lending portfolio lifecycle, leveraging a variety of techniques (e.g., supervised and unsupervised learning, Monte Carlo simulation, etc.)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 initiativesAssist in preparing materials for presentations, documents or business cases to senior management as neededAssist in conducting portfolio and ad-hoc analysis as neededAssist in project management activities as required.Qualifications/RequirementsAt least Master's degree in Statistics, Mathematics, Actuarial Science, Engineering, Operations Research, or another highly quantitative field with a track record of academic excellenceAt least 2 years' experience with developing data science and data engineering solutionsUnderstanding of credit risk concepts is an assetKnowledge of various statistical software skills including SAS, R, Python, etc.Proven analytic and problem solving skillsAbility to effectively communicate findings and insights in a clear and concise manner to different audiences with varying technical backgroundsAbility to translate highly technical concepts into actionable business solutionsExcellent oral and written communication skills.Strong collaboration, teamwork skills.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 solutionsExperience working with big dataWe'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. 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 .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.
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