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The position will be responsible for:
• Performing all model validation tasks including but not limited to independent model validation, annual model review, ongoing monitoring report review, required action item review, and peer review.
• Conducting governance activities such as model identification, model approval and breach remediation reviews to manage model risk.
• Providing hands-on leadership for projects pertaining to statistical modeling and AI/ML approaches; and providing methodological, analytical, and technical support to effectively challenge and influence the strategic direction and tactical approaches of these projects.
• Communicating and working directly with relevant modeling teams and their corresponding Front Line Units (Global Information Security / Technology); and if needed, communicating and interacting with the third line of defense (e.g., internal audit) as well as external regulators.
• Writing technical reports for distribution and presentation to model developers, senior management, audit, and banking regulators.
• Acts as a senior level resource or resident expert on analytic/quantitative modeling techniques used for managing Information Security risk and Technology risk.
Master’s degree in related field or equivalent work experience
• PhD or Masters in a quantitative field such as Computer Science, Engineering, Mathematics, Physics, or Statistics.
• Strong knowledge of Information Security best practices, principles, technologies, associated risks and attack vectors.
• Previous experience in Technology and Cyber Security across multiple incident or privacy disciplines.
• Professional Infrastructure domain experience within Risk, CTO, and/or Global Information Security.
• Strong knowledge of the NIST Cybersecurity Framework.
• Advanced understanding of security threats, vulnerabilities, exploits, attack vectors, malware, and digital forensics. Certificates in cybersecurity risk such as CISSP, Security+, CRISC, CISM will be a plus.
• Strong knowledge of tools and models used to aid core technology, employee experience and data management.
• Solid 3+ years of experience and knowledge with AI/ML and statistical modeling techniques, applying AI/ML techniques such as neural networks, random forest, GBM, SVM, Graphical models.
• Hands-on experience with deep learning architectures using open-source toolkits in Python, PySpark, PyTorch.
• Fluency with SQL on one or more relational databases such as Microsoft SQL Server, MySQL, Postgres or Oracle is a plus. Understanding of the Hadoop platform (e.g., MapReduce, Hive, Impala, Spark, Flume, Kafka) and related Big Data technologies will also be a plus.
• Excellent written and oral communication with stakeholders of varying analytic skills and knowledge levels.
• Critical thinking and ability to independently and proactively identify/suggest/resolve issues.
• Motivated to continuously research and share latest information security threats and trends to keep up with advancements.
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