Wealth Management-Operations-Business Intelligence & Applied AI-New York-Vice President

Goldman Sachs•New York, NY

47d•Onsite

About The Position

The Wealth Management Operations Division is seeking an experienced Vice President to lead the Applied AI Program and low code initiatives, driving the strategic convergence of advanced AI capabilities and cross-functional analytics to deliver measurable operational, risk, and experience improvements across the division. You will be responsible for enhancing operational performance through the widespread use of advanced engineered prompts within the firm's out-of-the-box AI solutions, while simultaneously leading and evolving the division's business intelligence function — encompassing data lifecycle management, analytics strategy, and the exploitation of low-code tools to create business value. You will design, develop, and deploy sophisticated human-in-the-loop "AI Assistants" through a controlled, risk-averse lifecycle — from ideation and prompt engineering through piloting, governance review, and scaled production rollout. In parallel, you will enhance and establish cross-functional analytics initiatives, address developments in key strategic data architecture, and ensure BI capabilities are tightly aligned with the Wealth Management Division's target operating model. You will collaborate with business stakeholders, Operations core BI teams, Technology, Risk & Compliance, and senior leadership to define unified roadmaps, prioritize initiatives, and implement scalable AI and BI solutions aligned with organizational goals.

Requirements

Minimum 7 years of progressive experience in applied AI, business intelligence, data analytics, or a related discipline within a fast-paced, complex environment (financial services or wealth management preferred).
Proven track record in AI solution design and deployment, including prompt engineering, human-in-the-loop system design, and responsible AI practices.
Demonstrated experience leading BI teams and analytics programs, including data lifecycle management, reporting platform strategy, and self-service/low-code tool adoption.
Strong understanding of data architecture, data governance, and data quality frameworks.
Experience building and presenting business cases with ROI analysis and KPI frameworks to senior leadership.
Exceptional ability to collaborate across business, technology, risk, and operations teams in a matrixed organization.
Familiarity with enterprise AI platforms (e.g., Microsoft Copilot, OpenAI enterprise solutions) and BI platforms (e.g., Tableau, Power BI, Alteryx, or similar).
Strong knowledge of governance, data privacy, and regulatory compliance requirements relevant to financial services.

Nice To Haves

Experience in Wealth Management or Financial Services operations and technology.
Hands-on experience with LLM-based applications, retrieval-augmented generation (RAG), and agentic AI frameworks.
Familiarity with low-code/no-code development platforms and their application in analytics and workflow automation.

Responsibilities

Define and lead the Applied AI Program vision and strategic roadmap, aligning AI Assistant development priorities with division-wide operational, risk, and experience objectives.
Drive widespread adoption of advanced engineered prompts within the firm's approved AI platforms (e.g., enterprise copilots, LLM-based tools), establishing best practices, prompt libraries, and reusable templates that maximize out-of-the-box solution value.
Design and deliver sophisticated human-in-the-loop AI Assistants that augment employee and client-facing workflows, ensuring appropriate human oversight, escalation paths, and feedback loops are embedded by design.
Establish and enforce a controlled, risk-averse AI solution lifecycle, encompassing use case intake, feasibility assessment, prompt engineering, testing & validation, risk review, pilot deployment, performance monitoring, and production scaling.
Continuously modernize the division's applied AI approach by monitoring emerging AI patterns (e.g., agentic workflows, retrieval-augmented generation, multi-modal prompting), assessing fit-for-purpose use cases, and driving implementation playbooks from pilot to production.
Lead and evolve the Wealth Management Division's Business Intelligence function, enhancing and establishing cross-functional analytics initiatives that deliver actionable insights to business stakeholders.
Own the data lifecycle management strategy, ensuring data quality, lineage, governance, and accessibility standards are maintained across all BI assets and reporting platforms.
Exploit low-code and self-service analytics tools to democratize data access, accelerate report development, and empower business users to derive value independently.
Address developments in key strategic data architecture, partnering with Technology to ensure the division's data infrastructure supports current and future analytical and AI workloads.
Align Operations BI strategy with the Wealth Management Division target operating model, working in close partnership with Operations core BI teams and Technology to harmonize priorities, tools, and methodologies.
Work closely with business representatives to ensure key decisions and progress are made in line with divisional strategic objectives and operating model requirements.
Develop robust business cases for new AI Assistants, BI enhancements, and analytics products, including financial justification (ROI), efficiency gains, risk reduction metrics, and experience improvement KPIs.
Lead and empower cross-functional teams — including business analysts, data engineers, prompt engineers, BI developers, UX designers, and subject matter experts — to deliver complex solutions ensuring strategic alignment and successful outcomes.
Foster strong partnerships with Data & Analytics, Engineering, Risk & Compliance, Information Security, PMO, HRIS, and business line leaders to ensure seamless execution and integration across both the AI and BI portfolios.
Uphold and ensure adherence to governance, data privacy, and regulatory compliance standards across all AI and BI products and initiatives.
Strategically manage vendor relationships, encompassing platform evaluation, selection, contract negotiation, and ongoing performance oversight for both AI and BI tooling.
Identify and drive synergies between the Applied AI and BI programs, leveraging BI data assets and analytics capabilities to inform AI Assistant design, and using AI to enhance BI workflows (e.g., natural language querying, automated insight generation, anomaly detection).