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Quantitative Risk Modeler
Ref No.: 18-02951
Location: New York, New York
Position Type:Direct Placement
Start Date: 09/24/2018
Our diversified asset mgmt client with offices in midtown is looking to hire full-time a Risk Mgmt Associate with a strong background in Python.

Seeking an experienced modeling expert interested in joining the Risk Management and Quantitative Business Modeling team focused on variable annuity models. Will join a dynamic intellectually stimulating team working on the cutting edge of insurance investments.

- Lead, maintain and develop our client's variable annuity models. Variable annuity models are stochastic models with actuarial inputs (like mortality curves, lapse behavior, withdrawal behavior, annuitization behavior and the interactions thereof etc.) against the backdrop of stochastic market projections (like equity returns, bond returns, and swap/treasure curve evolution through time)
- Over time, directly manages the economic model for a key investment at our client.
- Partners and interfaces with our client's Private Equity deal team
- Advises various individuals across the company and some of its insurance investments to properly manage the model in the face of complex market environments

QUALIFICATIONS AND EXPERIENCE: (Academic, Professional, Relevant Job Knowledge)
- 3-5 years of experience; strong coding skills in an enterprise context & quantitative modeling skills on the derivatives/asset side or actuarial/liability side
- Must be proficient in coding in Python
- Modeling experience, preferably variable annuity modeling or stochastic modeling of insurance liabilities
- Quantitative background and approach to risk; actuary or strong mathematical background
- Full comprehension of stochastic market models, familiarity with insurance company considerations, modeling of actuarial behavior (e.g., AG43 guidelines and reserving, CTE 95 assets, RBC capital, statutory accounting principles)
- Outstanding communication skills, with the ability to articulate and present complex information to key internal and external stakeholders in a clear and concise manner
- Optional: Masters in Finance or Math