This job is with S anticipate capacity/quality risks; influence outcomes through planning and constructive challenge in ambiguous situations. Embed continuous improvement into routines by improving playbooks/SOPs/prompt libraries and driving adoption. Partner with stakeholders to identify and shape high-impact use cases, supporting testing/adoption/rollout with governance, controls, and change management. Fosters a critical thinking mindset challenging assumptions and the status quo to generate insights that shape market views and strategic decisions. Model enterprise behaviors : Discovery, Integrity, and Partnership including human-centric leadership alongside AI-enabled change. Core Analytical escalate emerging risks early. Embed responsible AI use in workflow process. Drive controlled automation/agentic workflows to remove low-leverage work, defining requirements/ controls and partnering with Data/Engineering to scale safely while setting expectations for ongoing monitoring and human oversight. Compensation/Benefits Information: ( This section is only applicable to US candidates:) S delivers high quality with limited oversight. Strong collaboration/communication; influences through credibility and constructive challenge . Proven coaching/mentorship; develops juniors through feedback and quality review and reinforces human accountability in AI-enabled work. Continuous improvement mindset with evidence of simplifying processes through standardization , tooling, and automation. Comfortable with ambiguity and change, adapting quickly as processes/tools evolve. Ability to scale automation/agent workflows by defining problems, supporting testing/UAT, identifying controls, and enabling adoption. Core Analytical translates complexity into decision-useful narratives grounded in evidence and judgement. Strong understanding of the financial services environment and ability to connect developments to emerging risk themes. Practical AI fluency: experience embedding GenAI/LLMs and agentic workflows to increase productivity/insight as an enabler of human expertise , paired with disciplined validation, governance, and judgement. Strong analytical tool capability; willingness to learn data/automation tools to oversee AI-enabled production. Stakeholder consistent adherence to methodology /documentation/confidentiality expectations. Sound judgement on responsible AI/automation (validation, bias/hallucination awareness, data protection, attribution, approved boundaries). Additional Information An S
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