As a Regulatory Strategy Associate within the Compliance, Conduct and Operational Risk (CCOR) organization, you will apply analytics, AI-enabled business intelligence, Machine Learning, and GenAI to solve real business problems within regulatory engagement and governance. You will play a pivotal role in modernizing how teams manage regulatory interactions and how senior stakeholders consume insights by delivering AI-enabled reporting and analytics solutions, including governed metrics, SQL-driven data products, and AI-integrated dashboards. To be successful in the role, you will need strong problem-solving and communication skills, an ability to translate business needs into actionable analytical solutions, and genuine curiosity about artificial intelligence.

In this role, you will be responsible for collaborating across the firm, engaging with diverse departments such as Lines of Business/Functions, Compliance, Risk, Technology, Finance, and senior governance stakeholders. You will cultivate expertise in the firm’s regulatory agenda and acquire a comprehensive understanding of how governance is managed at a firm-wide level. Additionally, you will have the opportunity to provide insights to senior stakeholders up to the Operating Committee level.

Job Responsibilities

• Write and optimize SQL queries to deliver recurring reporting, ad-hoc analytics, and timely responses to stakeholder questions across regulatory engagement topics (regulatory issues, engagements with regulators, meetings, and requests).
• Develop, publish, and maintain stakeholder-facing dashboards and analytics (e.g., Tableau and/or ThoughtSpot), ensuring consistent definitions, logic, and user experience for senior audiences.
• Contribute to the development and enhancement of AI-enabled business intelligence assets (e.g., Databricks, ThoughtSpot, Tableau Pulse), including semantic layer buildout and governed metric definitions.
• Partner with stakeholders to define and maintain governed metric definitions and semantic layers to enable consistent KPI logic and scalable self-service analytics.
• Identify, evaluate, and help prioritize opportunities where Machine Learning and GenAI can add value, in partnership with stakeholders and developers.
• Support requirements gathering activities, including drafting mockups, user stories, and acceptance criteria, and help maintain and prioritize the product backlog.
• Support AI prompt and instruction development, testing of changes, and monitor performance and quality in partnership with stakeholders.
• Support automation and transformation of new and existing reporting sourced from multiple regulatory systems using tools such as Tableau and Alteryx.
• Build strong relationships with partners and senior leaders across the firm to drive delivery, adoption, and continuous improvement of analytics and reporting capabilities.

Required Qualifications, Capabilities, and Skills

• Bachelor’s degree in a quantitative, engineering, computer science, statistics, or related technical field with 2+ years of relevant work experience.
• Strong SQL skills, including querying, joining datasets, validating results, troubleshooting data issues, and translating analysis into clear stakeholder-facing insights.
• Experience building, maintaining, or enhancing dashboards or recurring reports using Tableau, ThoughtSpot, Power BI, Qlik, or a similar business intelligence / visualization tool.
• Strong written and verbal communication skills, with the ability to explain data, technology, and analytical concepts clearly to both technical and non-technical stakeholders.
• Strong interest in AI-enabled analytics and automation, with a business-outcome mindset and willingness to learn emerging tools, methods, and governance expectations.
• Detail-oriented, proactive, and organized, with the ability to manage multiple priorities, deadlines, and stakeholder requests in a fast-paced environment.

Preferred Qualifications, Capabilities, and Skills

• Experience with Databricks, governed data environments, or AI-enabled analytics tools.
• Exposure to maintaining or improving LLM assistants, agents, prompt instructions , or AI-enabled business intelligence assets, along with an understanding of semantic layers, governed KPI definitions, or self-service analytics enablement.
• Background in regulatory, risk, compliance, control, finance, audit, or other governance-oriented business processes.