Senior Asset Modelling & Forecasting - Flexible Hours

auxmoney GmbH; Dublin; Hybrid; EUR 90,000 - 150,000; Full time

Benefits offered by this job

Flexible hours

Home office policy

Autonomy

Growth opportunities

Health insurance

Job summary

auxmoney GmbH is seeking a senior quantitative professional to own forecasting models for unsecured consumer loan portfolios, while improving monitoring, attribution analysis, and stress testing. You will work closely with Credit Risk to translate data into actionable business decisions in a tech-led fintech setting.

Candidates should bring strong modelling experience, IFRS 9 awareness, and hands-on Python and SQL skills, with a practical approach to real-world data and clear communication.

Qualifications

• Solid experience building credit portfolio or asset performance models in banking, fintech, or consumer finance.
• Hands-on Python and SQL with statistical, econometric, or machine-learning methods.
• IFRS 9 / ECL concepts knowledge to collaborate effectively with experts.
• Ability to define defaults, construct cohorts, manage backfills.
• Ability to explain modelling choices to non-modellers clearly.
• Fintech, tech-led environment with a mindset for continuous improvement.

Responsibilities

• Own forecasting models for unsecured consumer loan portfolios.
• Run and improve monitoring, surfacing drift, instability, and early warning signals.
• Lead attribution analysis decomposing actual vs forecast variances into drivers.
• Build stress-testing and scenarios for planning and decisions.
• Ensure governance with documentation, validation checks, and reproducible runs.
• Improve data and pipelines with reporting, automation, and data quality.

Skills

Strong modelling background

Technical excellence

IFRS 9 awareness

Comfort with real‑world data

Clear communicator

Fintech and innovation driven

Tools

Python

SQL

Job description

auxmoney GmbH is seeking a senior quantitative professional to own forecasting models for unsecured consumer loan portfolios, while improving monitoring, attribution analysis, and stress testing. You will work closely with Credit Risk to translate data into actionable business decisions in a tech-led fintech setting.

Candidates should bring strong modelling experience, IFRS 9 awareness, and hands-on Python and SQL skills, with a practical approach to real-world data and clear communication.