Senior Audit Manager - Model Validation

About the role

Independent preparation and planning of Non-IT audits assignments and lead end to end audit engagements. Perform deep-dive technical reviews of complex mathematical models, including machine learning architectures and traditional quantitative finance models, while functionally challenging model assumptions and calibration techniques used by quantitative development teams.

What you'll do

• Independent preparation and planning of Non-IT audits assignments and lead end to end audit engagements.
• Perform deep-dive technical reviews of complex mathematical models, including machine learning architectures and traditional quantitative finance models (e.g., credit risk, market risk, or valuation models).
• Evaluate the mathematical soundness, data lineage, and preprocessing pipelines of AI/ML models to ensure the integrity of inputs, training data, and model outputs.
• Functionally challenge model assumptions, mathematical formulations, and calibration techniques used by quantitative development teams.
• Draft comprehensive audit reports and coordinate findings and recommendations with stakeholders.
• Coordinate and guide audit team members during audit engagements, including performing audit quality reviews.
• Deliver concise and impactful management reports on audit outcomes.
• Independent support of internal projects in line with relevant regulatory requirements (e.g., MaRisk/KWG).

What you'll need

• A higher education degree, preferably in Finance, Economics, Business Management, or Law.
• 5+ years of relevant work experience in-house or in an audit/consultancy firm in banking (related to MaRisk/KWG/GwG etc.).
• Experience as an auditor or consultant in auditing techniques (ToD and ToE).
• Experience leading audit engagements including quality audits reviews and management reporting.
• Very good knowledge of regulatory standards.
• Strong theoretical and practical understanding of advanced statistics, probability theory, econometrics, and machine learning algorithms (both supervised and unsupervised learning).
• Proven experience in auditing or developing quantitative models, backtesting, stress testing, or sensitivity analysis within a financial or highly regulated context.
• Fluent in both English and German communication skills.

Nice to have

• A good understanding of audit software.
• Experience in reviewing code and model implementations using standard data science libraries (e.g., Pandas, NumPy, Scikit-Learn, TensorFlow, or PyTorch).

What they offer

• Competitive salary and a variable remuneration program.
• Learning & development budget of €1000 per year and a transparent growth framework.
• Home office budget.
• 28 vacation days, increasing by 2 days after 2 years and 3 days after 3 years.
• Monthly meal allowance and Deutschland ticket subsidy.
• Opportunity to work abroad for up to 12 weeks per year.