VP - Analytics

Working at the intersection of quantitative modelling, software engineering and investment analytics, you will lead the continued evolution of a proprietary in-house platform while remaining deeply involved in architecture, coding and model development.

Client Details

Our client is a leading institutional investment organisation.

Description

• Own and enhance a proprietary liquidity and return modelling framework covering both public and private market investments.
• Lead the development of institutional-grade analytical applications built in Python and SQL, supporting portfolio management and balance sheet modelling activities.
• Design and oversee enterprise data architecture, ETL processes and system integrations across investment, performance and accounting platforms.
• Deliver scalable analytics and reporting solutions used by senior leadership and governing committees for investment decision-making.
• Manage external development resources whilst establishing engineering standards, development governance and technical best practice.

Job Offer

• Opportunity to work on complex public and private market portfolios within a sophisticated institutional investment environment.
• Competitive package and long-term career growth within a high-performing investment team.
• 8-10+ years' experience within a sovereign wealth fund, pension fund, endowment, insurance asset manager, secondaries investor or institutional investment platform.
• Demonstrated experience developing or maintaining quantitative models for liquidity forecasting, portfolio cash flows, commitment pacing, return forecasting or asset allocation across public and private markets.
• Advanced hands-on programming experience in Python and SQL, with the ability to independently analyse, debug and enhance production code.
• Strong knowledge of investment data architecture, database technologies, ETL frameworks and Snowflake environments.
• Previous experience leading technical resources and working directly with investment professionals, portfolio analytics teams and senior stakeholders.