Corporate Finance - VP - Portfolio Analytics
Indexed description
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
- 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
- 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
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