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    Quantitative Financial Analyst - Woodland Hills, United States - Apollo Inc

    Apollo Inc
    Apollo Inc Woodland Hills, United States

    2 weeks ago

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    Description
    Position Overview

    Apollo is seeking a Quantitative Financial Analyst for its Woodland Hills, CA, office. This role is crucial as the Quantitative Development team maintains a suite of proprietary mortgage investment risk models developed in-house for financial reporting, risk measurement, pricing, and strategic business decisions. These models ensure underwriting consistency and accurate stress testing of our Consumer & Residential investment portfolio, making your contribution invaluable.
    • Analyze portfolio loan tapes, verifying data consistency and generating stratifications and analysis
    • Assess risk parameters of portfolios, deriving loss assumptions from historical performance
    • Running internal pricing & risk models
    • Perform ad-hoc requests for data analysis, query, etc., as needed.
    • Automating reporting and monitoring processes for existing transactions
    • Assist various trading needs, including macro trend analysis, asset allocation, optimizations, etc.
    Qualifications & Experience
    • Minimum Master's degree in a Quantitative background (statistics, machine learning, quantitative finance, financial mathematics, econometrics, physics, mathematics)
    • 1-3 years of professional experience working in a quantitative capacity
    • Efficient Python/C#/SQL programming skills, C++ programming skill is a plus
    • Experience handling large data sets
    • Financial fixed income knowledge, especially on US residential mortgages
    • Strong communication skills, both written and verbal
    • Ability to work in a fast-paced environment, under pressure, and deliver on time
    Pay Range
    $110,000 - $175,000

    The base salary range for this position is listed above. This position is also eligible for a discretionary annual bonus based on personal, team, and Firm performance. Compensation ranges are based on several factors including job function, level, and geographic location. Final offer amounts are determined by multiple factors including candidate experience and expertise, and may vary from the amounts listed here.


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