Credit Risk Modelling & Analytics Analyst

Moeve; Madrid; On-site; EUR 55,000 - 75,000; Full time

Job summary

Moeve in Madrid is seeking a risk modelling specialist to advance counterparty credit risk capabilities within the Modelling & Analytics team. You will build robust, transparent methodologies to measure exposure at trade, counterparty and portfolio levels across energy commodities, derivatives and physical contracts.

The role focuses on PD/LGD estimation, EL/UL metrics and automated reporting, with governance and audit readiness.

Qualifications

• 2–3 years of experience in quantitative risk, counterparty credit risk, market risk, or commodity trading analytics.
• Degree in Mathematics, Physics, Engineering, Statistics, Computer Science or related quantitative discipline.
• Strong programming skills in Python with NumPy, Pandas and SciPy; SQL experience desirable.

Responsibilities

• Develop and maintain methodologies to measure counterparty credit exposure at trade, counterparty and portfolio level across energy commodities, derivatives and physical contracts.
• Model PD/LGD estimation and integrate exposure profiles into EL/UL metrics for risk decision-making.
• Automate recurring credit risk calculations, controls and reporting with traceability and scalability.
• Document methodologies, data sources and limitations to support validation and governance.

Skills

Quantitative risk

Python

Monte Carlo

Statistical modeling

Risk analysis

Communication

Education

Mathematics/Physics/Engineering/Statistics/CS

Tools

NumPy

Pandas

SciPy

SQL

Job description

Moeve in Madrid is seeking a risk modelling specialist to advance counterparty credit risk capabilities within the Modelling & Analytics team. You will build robust, transparent methodologies to measure exposure at trade, counterparty and portfolio levels across energy commodities, derivatives and physical contracts.

The role focuses on PD/LGD estimation, EL/UL metrics and automated reporting, with governance and audit readiness.