Corporate Finance - VP - Portfolio Analytics

Abu Dhabi Investment Council (ADIC) is an institutional investment organization focused on managing and evaluating investments across asset classes, including private equity and infrastructure, while supporting portfolio analytics and corporate functions. Operating in the investment management sector, ADIC combines analytical rigor with practical decision support to help teams work from robust, dependable insight.

This role sits at the intersection of engineering, analytics, and portfolio insight. As Corporate Finance - VP - Portfolio Analytics, you will play a key role in strengthening the systems and analytical capabilities that support liquidity analysis and broader portfolio decision-making, working closely with investment and support stakeholders to ensure outputs are dependable, scalable, and fit for purpose.

Responsibilities

• Lead the technical development, engineering, and operational ownership of ADIC’s in-house liquidity model and supporting analytical applications.
• Write, optimize, and maintain production-grade code that underpins analytical workflows and model performance.
• Build and operate data pipelines that support the liquidity model and related analytics.
• Integrate ADIC’s data ecosystem, including Snowflake, source systems, FactSet, and internal databases, with the liquidity model.
• Partner with investment and support departments to deliver robust, reproducible analytics, reporting outputs, and ad-hoc data extractions.

Education

• University degree in Computer Science, Software Engineering, Data Science, Financial Engineering, Quantitative Finance, Mathematics or a related quantitative discipline
• Relevant technical certifications (e.g. Snowflake, AWS/Azure Data Engineering) or finance qualifications (CFA, CAIA) desirable but not required

Experience

• A minimum of 8 – 12 years of hands-on experience in data engineering, quantitative development or applied analytics, with at least 5 years building and maintaining production Python/SQL applications and data pipelines in a financial services or asset management setting.
• Hands-on experience with Snowflake, FactSet, and AWS or Azure cloud data platforms.
• Experience integrating internal databases with analytical applications or data pipelines, including work with internally built financial systems or applications.
• Experience with liquidity modeling, quantitative financial modelling on returns, and scenario analysis and Monte Carlo simulation.
• Understanding of liquidity metrics such as LCR.
• Experience applying production-grade coding standards, automated testing, and reproducible analytics practices.
• Experience working with senior management, investment teams, treasury teams, and risk teams.