Senior Risk Manager - Model Validation (AI/ML Models)

Job Description

Role Description DWS Group (DWS) is one of the world's leading asset managers with EUR 841bn of assets under management (as of 31 March 2023). Building on more than 60 years of experience, it has a reputation for excellence in Germany, Europe, the Americas and Asia. DWS is recognised by clients globally as a trusted source for integrated investment solutions, stability and innovation across a full spectrum of investment disciplines. We offer individuals and institutions access to our strong investment capabilities across all major asset classes and solutions aligned to growth trends. Our diverse expertise in Active, Passive and Alternatives asset management as well as our deep environmental, social and governance focus complement each other when creating targeted solutions for our clients. Our expertise and on-the-ground-knowledge of our economists, research analysts and investment professionals are brought together in one consistent global CIO View, which guides our investment approach strategically. The Risk platform is the independent risk oversight function of DWS. Model Risk is part of the Risk function and is designed to provide governance and control to manage a variety of models used in the Firm and associated risks. The Model Risk team works as a global organization with team members in New York, London and Frankfurt with a focus around validating, testing and overseeing the usage of models related to Corporate Risk (liquidity/economic capital) and Investment Risk for Liquid and Illiquid investment strategies. Your key responsibilities Leading the delivery of the validation Book of Work for all Artificial Intelligence (AI) and Machine Learning (ML) models across the organization Conducting model validations on the DWS models, both in-house and vendor models, based on regulatory guidance, internal policy and procedures and best industry practice and communicate findings and recommendations to model owners and prepare the model validation reports Working closely with Investment teams on topics including model assumptions and limitations to ensure models remain fit for purpose Participating in independent model reviews on complex topics in accordance with business needs and regulatory requirements Review ongoing model monitoring reports, identify potential model risk and document the findings to key stakeholders while evaluating the corrective actions Assist in building benchmark models used across the model validation team, design backtesting or other methodologies to test the conceptual soundness of model assumptions We are looking for: Proven experience in the field of Quantitative Risk Management associated to AI and ML Experience of AI and ML model development from across the Investments, Consulting or Banking industry with an understanding of concepts associated to validating or developing risk models Strong quantitative skills utilising at least one of Python or C++ Good understanding of valuation methods, capital markets, portfolio theory and risk management Excellent verbal and written communications skills -- previous experience of writing either technical documentation related to model validation or development or independent peer-reviewed research articles Educated to post-graduate degree level in a quantitative field such physics, mathematics, statistics, economics or engineering, or with relevant industry experience / professional qualification