Quant Modeler - Analyst/Associate

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