Quant Modeler - Analyst/Associate

Location Brookfield Place New York - 250 Vesey Street, 15th Floor Business - Wealth Solutions Brookfield Wealth Solutions ("BWS"; NYSE/TSX: BNT) is focused on securing the financial futures of individuals and institutions through a range of retirement services, wealth protection products and tailored capital solutions. Through our operating subsidiaries, we offer a broad range of insurance products and services, including annuities, personal and commercial property and casualty insurance and life insurance Brookfield Culture Brookfield has a unique and dynamic culture. We seek team members who have a long-term focus and whose values align with our Attributes of a Brookfield Leader: Entrepreneurial, Collaborative and Disciplined. Brookfield is committed to the development of our people through challenging work assignments and exposure to diverse businesses. Job Description Investment Analytics We are looking for a full-time quantitative modeler to join our dynamic and growing quantitative analytics team to focus on cash flow and analytics projections for various public and private securities. The individual is expected to develop quantitative analytics and perform financial modeling, as well as the ongoing business support for all analytics requirements from the BAM Insurance Solution team. This role requires both Python and SQL programming ability and comfort with emerging cloud-based technologies. You will work in a fast-paced, innovative and collaborative environment to build investment analytics infrastructure. In addition to building applications and analytics infrastructure, the candidate will support applications already built by the team, understand them and be able to debug when issues arise. Key Responsibilities Provides financial, analytical, modeling expertise to build quantitative models for business projects. Implement, back test and validate current asset models. Build visual tools for monitoring and adjusting model performance. Collaborate with developers to build a robust analytics platform including data processing, analytics and cashflow projections, portfolio monitor and reporting. Hands on modeling during the entire life-cycle Conducting tests to ensure the accuracy and effectiveness of the models Validating and recalibrating the models as needed Providing comprehensive documentation for the models Reviewing production results and providing analytical support for business decisions Requirements 2-4 years' experience in a quant modeling role, preferably in structured products Advanced degree in financial engineering, statistics, mathematics, or similar quantitative field Experience with structured credit (RMBS, CLOs, CMBS, ABS) Experience with mortgage credit modeling (prepayments, defaults, severities) Utilizing statistical models such as linear regression, logistic regression or time series model to estimate the relationship between outcome variable and risk factors, make predictions and forecast Proficiency with Intex and Bloomberg. Experience with Polypaths, QRM or Yieldbook is a plus Solid programing skills in Python, SQL, Excel/VBA Excellent interpersonal and communication skills, both written and verbal Ability to multi-task and work in a very fast-paced and team-oriented environment Salary Range: $115K - 150K Our compensation structure is comprised of a base salary and a short-term incentive program (cash bonus). Cash compensation tends to vary based on geography to account for local market conditions and is set to be market competitive. Compensation decisions are based on a number of factors including relative experience, overall years of experience, industry experience, education and designations Brookfield is committed to maintaining a Positive Work Environment that is safe and respectful; our shared success depends on it. Accordingly, we do not tolerate workplace discrimination, violence or harassment. We are proud to create a diverse environment and are proud to be an equal opportunity employer. We are grateful for your interest in this position, however, only candidates selected for pre-screening will be contacted.

Created: 2024-11-12