Asset Management - Institutional Strategy and Analytics - Insurance - Vice President

The Institutional Strategy and Analytics (IS&A) team within J.P. Morgan Asset Management (JPMAM) is a front office client facing group of professionals within asset management who have varied backgrounds in asset allocation, asset liability management (ALM), consulting, optimization, programming, and actuarial science. The IS&A team develops applications to provide asset allocation, capital management, risk management and other advisory services to institutional clients and prospects on a global basis. The IS&A team works primarily with insurance companies due to the complexity of insurance company investment constraints but also supports pension schemes and other institutional investors. Within JPMAM the IS&A team works closely with all investment teams as well as with the institutional salesforce.

Role Summary

You are a fit for this London based role if you have strong knowledge of insurance ALM, Solvency II, programming skills and would like to expand your career in investment management across all asset classes and institutional client types. You will work to help develop scalable investment management solutions for insurance companies, pension funds, and other institutional investors. The role involves optimization analysis, strategic asset allocation, stochastic modeling and development of our analytical toolkit. Most of the work will be UK focused but the role could have continental / international components, especially if you have the relevant language skills.

Job Responsibilities

• Enhancement of existing modeling platform – Work to adapt existing models to improve scalability, flexibility, and efficiency.
• Development of new analytical capabilities – Help implement new models for constrained asset allocation including tactical portfolio optimization, using various data sets to generate sales insights, and developing other applications as needed.
• Completion of client advisory assignments – Analysis for clients including completing analysis to meet their needs, presentation of results, and incorporation of revisions/extensions as needed.
• Development of intellectual capital – Help produce high quality research/analysis in response to industry developments.

Required qualifications, capabilities and skills

• Bachelors or Master’s degree in a quantitative/analytical discipline such as actuarial science, computer science, mathematics, physics, operations research, statistics, engineering or equivalent experience.
• Quantitative analysis and software engineering – Deep knowledge of quantitative analysis techniques used for investment management and risk management. Able to undertake and oversee the development of production quality code in Python including the specification of modelling requirements.
• Investment management – Understanding of all major asset classes that UK/European institutional investors (especially insurers) invest in, including expected return, market risk, credit risk, structure, liquidity, cash flow characteristics, diversification benefits, etc. This includes public and private assets.
• Industry knowledge – Expert understanding of factors that constrain pension funds including liabilities, accounting, risk appetite, funding level, etc. The primary focus is the UK and European pension market, but pension background in the Middle East and South Africa is helpful.
• Communication – strong verbal and written communication skills and extensive work experience preparing high quality presentation materials for clients

Preferred qualifications, capabilities and skills

• Experience with object-oriented programming and sound software engineering practices and working familiarity with IFRS accounting, insurance capital models (such as Solvency II), or defined benefit pensions.
• Ability to apply basic investment management concepts, such as efficient frontiers, capital constraints, risk attribution and risk limits, factor investing, etc.
• Familiarity with basic asset classes (e.g., corporate bonds, CLOs, private equity) and their expected return, market risk, credit risk, structure, liquidity, cash flow characteristics, diversification benefits, etc.
• Coursework or work experience covering linear and non-linear optimization (including the formulation of problems, development of constraints, and use of software to solve these problems, especially mixed integer optimization problems), advanced statistical methods, econometrics, and stochastic processes.