Job Description
We are currently looking for ambitious graduates to join one of the worlds leading Investment Managers based in their London office.
Currently managing over £200bn in AUM, this firm develop customised investment strategies that address unique objectives, requirements and tolerance for risk. They develop solutions by leveraging their risk management tools and utilising a highly disciplined investment process that relies on fundamental analysis.
Predominant role is working within Investment Solutions to support the Investment
Management team in delivering asset–liability modelling (ALM), strategic asset allocation
(SAA) analysis and risk analytics for funds. The role focuses on preparing and validating
datasets, running and documenting model analyses using a software suite,
producing high-quality client materials, and potentially assisting with RFP/RFI responses,
demos and meetings. The analyst will learn about investment process and use its
proprietary software tools.
Investment Management Support
* Assemble, clean and reconcile input datasets (assets, liabilities, constraints) for ALM/SAA studies; maintain auditable workflow.
* Run model analyses under direction (scenario sets, sensitivity tests, stress runs) and produce clear exhibits (tables, charts) for clients.
* Document assumptions, methodology and results; maintain project files, trackers and version-control hygiene.
* Prepare portfolio- and benchmark-level risk/return summaries to support investment proposals and client reviews.
* Contribute to timely delivery of analytics to support the investment team’s sales process and client discussions.
Technical & Modelling Support
* Develop a strong understanding of the various asset classes and product lines that the firm manages and the services it provides.
* Develop working proficiency with Conning’s modelling tools (e.g., economic scenario generation, portfolio analytics) and internal utilities.
* Build light automation (Python/R/Excel VBA/SQL) for recurring data preparation and quality checks.
* Contribute to periodic calibration/assumption reviews and maintain the assumptions library with proper documentation.
Requirements
* Degree in a quantitative discipline (Actuarial Science, Finance, Economics, Mathematics, Statistics, Engineering, Computer Science, etc.).
* Solid understanding of core capital markets concepts
* Hands-on skills in Excel (advanced), PowerPoint; working knowledge of Python (SQL desirable).
* Clear written and verbal communication; ability to produce client-ready exhibits with strong attention to detail.
* Team-oriented, organised and proactive; able to manage multiple tasks and deadlines.