ALM Risk Analyst

Company/ Firm Name

USS

Location

London, UK

Published Date

8 September 2021

About the job:

The Universities Superannuation Scheme (USS) has circa 396,000 members, and over £60 billion in assets, we’re one of the largest private pension schemes in the UK and in the top 50 worldwide. Established in 1974, we’re entrusted by over 350 higher education sector employers to manage and administer the pension scheme and its investments through our two companies, Universities Superannuation Scheme Limited and USS Investment Management Limited.


Our purpose

Working with Higher Education employers to build a secure financial future for our members and their families.

The role
To support and build on the capability within the Strategic Advice and ALM function associated with all ALM related activity. More specifically this relates to areas of analysis, advice and support pertaining to the triennial valuation process, stochastic analytics and liability cash flow dynamics.

This role is intended to assist in the alignment of the asset strategy and portfolio construction with the overarching and long-term liability dynamics on the DB side, and to assist in the development of the Glidepath and life-style options associated with the DC side.

The role will also ensure the bridge between the Funding Strategy team and USSIM is maintained and developed, as well as working with the ISA and Risk (PAIR) functions to develop the front-line risk framework.

The role provides support and development to all ALM related activities, including valuation support, LDI and long term stochastic risk modelling in the context of portfolio construction and management.


Key responsibilities


Delivering Results


• Works with ISA and PAIR to embed stochastic ALM analytics into the front- and second-line risk frameworks across DB and DC.
• Supports the integration of the liabilities into the asset allocation process, as well as the liability hedging programmes into the portfolio construction process (DB).
• Supports the ongoing development of the DC Glidepath, life-style options and potential future post-retirement offering
• Supports the Head of Strategic Advice and ALM and Funding Strategy teams in the scheme triennial valuation process
• Supports the CEO and USSIM Asset Allocation Committee (“AAC”) in portfolio construction and the long-term strategic asset allocation decision process
• Remains abreast of investment market and pension related developments and actively incorporates knowledge in the development of strategic initiatives
• Supports the preparation of committee papers for the relevant boards, coordinating and liaising with Head of Strategic Advice and ALM on content and other requirements.
• Continue to improve the consistency of market data used for analytics originated by ISA
• Ensures the asset inventory and model compliance are up to date for internally developed ALM models


Managing Resources


• Maintains constant dialogue with the Senior ALM Specialist, Head of Strategic Advice and ALM and Funding Strategy Team
• Operates a quality assurance process to ensure consistency and accuracy across the team
• Remains abreast of wider initiatives, particularly among Funding Strategy, CEO and PAIR functions
• Ensures all process documents are up to date for the most efficient use of resources


Your experience

Essential


• A great attitude – proactive and enthusiastic
• Attention to detail
• Previous experience in investment risk and stochastic analysis
• Familiarity with UK defined benefit pension topics
• Ability to communicate effectively in both written papers and oral presentations
• Familiarity with quantitative methods (statistics, econometrics, etc.)
• Intellectual curiosity – willingness and ability to investigate and develop new ideas
• Proficient at prioritisation, project organisation, and management of multiple workstreams

Desirable


• Undergraduate qualification with economics, finance and statistic content and/or progress towards post-graduate investment/actuarial qualification (e.g. CFA, FIA)
• Good understanding of institutional asset classes (including LDI, equities, credit and private markets)
• Good understanding of macroeconomics, actuarial and investment theory
• IT and programming skills (e.g. Excel, VBA and Python)