Andesite Partners is delighted to be exclusively working with a leading European investment platform backed by a integral alternative asset manager. The business invests across complex credit and real asset opportunities, including non‑performing loans, structured transactions, and opportunistic real estate.
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The Madrid team is looking to hire an
Investment Analyst or Associate (Underwriter)
to support the evaluation and execution of investment opportunities. This role offers hands‑on exposure to underwriting, modelling, and data‑driven investment decision‑making within a highly analytical environment.
The Role
You will sit within the underwriting and analytics team, working closely with senior investment professionals on live transactions. The role is heavily analytical and technical, with a strong emphasis on modelling, data, and problem‑solving.
Key Responsibilities
Build and maintain financial models across:
Loan portfolios (performing and non‑performing)
Real estate cash flow and valuation
Structured credit transactions (e.G. securitisations, financing structures)
Perform scenario analysis and stress testing to assess risk/return dynamics
Support investment decision‑making through detailed quantitative analysis
Work with large datasets to support underwriting and portfolio analysis
Build and enhance internal tools and databases for investment workflows
Contribute to automation of processes to improve efficiency and scalability
Apply coding and data tools to streamline analysis and reporting
Support the preparation of investment memos and presentations
Translate complex analysis into clear, structured outputs for internal stakeholders
Candidate Profile
1–3 years’ experience in a highly analytical environment such as:
Quantitative / analytics xhfqzwm roles within financial services
Credit funds, structured finance, or data‑heavy roles
Demonstrated coding ability (e.G. Python, C#, C++)
Experience with data tools such as SQL, Power BI or similar
Comfortable working with large datasets and building analytical solutions
Strong problem‑solving mindset with a genuine interest in quantitative work
Academic Background
Degree from a top university in a quantitative discipline, such as:
Mathematics
Physics
Computer Science
Strong academic track record and evidence of analytical rigour
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