Your role

Are you an expert in data analytics? Do you enjoy understanding models and their background? Are you organized with an eye for detail? We’re looking for someone like that to:

  • review and challenge models used in operational risk management
  • assess the conceptual soundness and appropriateness of different models and perform related outcome, impact and benchmark analyses
  • run analyses on implementations to assess their correctness and stability
  • carry out and document independent model validation in line with regulatory
  • requirements and internal standards
  • interact and discuss with model users, developers, senior owners and governance bodies
  • support regulatory exercises

Your team

You will be working in Model Risk Management & Control (US) function within the US Chief Risk Officer organization. Our role is to understand and assess the risks associated with the use of models throughout the firm. We focus on models used to monitor operational risks such as money laundering, rogue trading or market manipulations, as well as artificial intelligence models used across the bank. You are responsible for identifying corrective actions that promote model risk management process improvements and ensuring the timely remediation of identified issues. You will interface with key stakeholders, US regulators and internal audit to discuss justification and reasoning behind validation and review findings.

Your expertise

The role requires a mix of expertise in statistics, information technology and specialist knowledge in monitoring of compliance and the use of artificial intelligence within the banking industry. Ideally, you have skills and experience in these areas but an eagerness to further develop your existing expertise is more important.

  • a Masters (MSc) or PhD degree in a quantitative field (e.g. computer science, statistics, mathematics, physics, engineering or economics)
  • Hands on experience in developing or validating statistical/mathematical models
  • expertise in data assembling and analysis, computational statistics, anomaly detection or machine learning including relevant programming skills, for example in R, Python, Java, C++
  • expertise in SQL, i.e. for querying and manipulating large databases
  • strong writing skills and a structured working style
  • familiarity with the global financial industry and its compliance and operational risks
  • able to explain technical concepts in simple terms to facilitate collaboration
  • willing to create your own brand in the group and companywide
  • skilled at constructive criticism (you have the human touch)
  • motivated, well organized, and able to complete tasks independently to high quality standards and delivering to tight timelines
  • fluency in English (written and oral)

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