Quantitative Treasury & ALM Risk Intern

ebury anz; Madrid; On-site; EUR 25,000 - 35,000; Full time

Job summary

Ebury Anz in Madrid seeks a Quantitative Treasury & ALM Risk Intern to work in a hybrid setup (4 days in office, 1 day from home). In this role, you'll take ownership of key operations and gain insights into global treasury management.

Your responsibilities include analyzing liquidity reports, executing interest rate hedges, and optimizing operational code using Python and SQL. Ideal candidates are final year students or recent graduates in quantitative disciplines with a strong interest in finance.

Qualifications

• Final year student or recent graduate in Mathematics, Physics, Engineering, Quantitative Finance, Statistics, or Finance.
• Demonstrable foundational knowledge in Python and SQL.
• Strong passion for quantitative financial mathematics.

Responsibilities

• Take ownership of crucial Business As Usual (BAU) operations.
• Prepare and analyze the daily liquidity report.
• Assist in the execution and monitoring of interest rate hedges.
• Support the mapping of interest rate risk through DV01 analysis.
• Contribute to the optimization of daily operational code using Python and SQL.

Skills

Python (NumPy, Pandas)

SQL

Quantitative financial mathematics

Analytical and problem-solving skills

Communication skills

Education

Final year student or recent graduate in a quantitative discipline

Job description

Quantitative Treasury & ALM Risk Intern

Location: Madrid Office – Hybrid: 4 days in office, 1 day working from home per week

What you'll do

• Take ownership of crucial Business As Usual (BAU) operations, gaining a frontline understanding of global treasury management and real-world financial markets.
• Prepare, analyze, and optimize the daily liquidity report, acting as a key player in monitoring the company's financial health and liquidity risk.
• Assist in the execution and monitoring of interest rate hedges, gaining hands‑on exposure to practical risk mitigation strategies.
• Support the mapping of interest rate risk through DV01 analysis and the automation of hedging strategies.
• Contribute to the refactoring and optimization of our daily operational code and reports using Python and SQL.
• Learn to document and present quantitative findings and daily key metrics to the team.
• Brainstorm and contribute ideas to innovate and streamline current daily processes.

What you'll need

• Final year student or recent graduate in a quantitative discipline (Mathematics, Physics, Engineering, Quantitative Finance, Statistics, etc.), Business, or Finance.
• Academic or demonstrable foundational knowledge in Python (NumPy, Pandas) and SQL is highly valued to help automate daily tasks.
• Eagerness to learn, with a strong interest in corporate treasury, liquidity management, and data analysis.
• A strong passion for quantitative financial mathematics and quantitative analysis.
• Strong analytical and problem‑solving skills, with a keen eye for detail in daily reporting.
• Communication, documentation, and presentation skills with the ability to explain complex concepts clearly and concisely.
• Curiosity and a drive to learn complex financial concepts.
• Ability to work effectively in a collaborative team environment.
• Confident communication in English, both written and spoken.
• Open to candidates from diverse academic backgrounds, provided they demonstrate a strong interest and aptitude for quantitative finance and risk modeling.

Why Ebury?

• Experience a startup culture within a stable, global company.
• Learn from and collaborate with highly skilled quantitative professionals.
• Shape your own career path with flexible development opportunities.
• Gain rapid responsibility and ownership of meaningful projects.
• Work with advanced quantitative risk management techniques and methodologies.

We believe in inclusion. We stand against discrimination in all forms and are against the intolerance of differences that makes us a modern and successful organisation. At Ebury, you can be whoever you want to be and still feel a sense of belonging no matter your story.