Asset & Wealth Management-WM Ops Transformation-Associate--Bengaluru

Asset & Wealth Management-WM Ops Transformation-Associate--Bengaluru

WEALTH MANAGEMENT 

Across Wealth Management, Goldman Sachs helps empower clients and customers around the world to reach their financial goals. Our advisor-led wealth management businesses provide financial planning, investment management, banking and comprehensive advice to a wide range of clients, including ultra-high net worth and high net worth individuals, as well as family offices, foundations and endowments, and corporations and their employees. Our consumer business provides digital solutions for customers to better spend, borrow, invest, and save. Across Wealth Management, our growth is driven by a relentless focus on our people, our clients and customers, and leading-edge technology, data and design.

Operations

Operations is a dynamic, multi-faceted division that partners with all areas of the firm to deliver banking, sales and trading and asset management capabilities to clients around the world. Alongside this vital service delivery role, Operations provides essential risk management and control, preserving and enhancing the firm’s assets and its reputation. Operations  partners with all areas of the firm to deliver banking, sales and trading and asset management capabilities to clients around the world. Alongside this vital service delivery role, Operations provides essential risk management and control, preserving and enhancing the firm’s assets and its reputation. Operations span all product lines and markets, and functions.

Your Impact – 

As a Process Modernization Associate, you will partner directly with operations teams that support the firm’s wealth management business. This role will lead end-to-end assessments of existing workflows, technology stacks, and control frameworks, using AI alongside traditional process improvement methodologies to deliver actionable recommendations to enhance efficiency, mitigate risk, and improve service.

Our Impact – 

PWM Operations supports PWM Private Wealth Advisors (PWA) globally. PWAs are responsible for advising ultra-high net worth individuals on strategies to build and protect their financial assets through customized advice and services.PWM Operations is instrumental in meeting our clients' needs and is responsible for several key processes which include account opening, asset transfers, client servicing, execution services, performance measurement and reporting of Goldman-custodied assets and away-custodied assets.

Key Responsibilities

Process Discovery & Analysis

• Conduct structured engagements with operations teams to map and document current-state processes, including manual workflows, system dependencies, and data flows.
• Develop and utilize a standardized organizational taxonomy to identify and solve for cross-functional patterns and inefficiencies 
• Perform detailed process mining and data analysis to identify bottlenecks, redundancies, and failure points.
• Evaluate the existing technology stack (platforms, tools, integrations) for fitness-for-purpose, scalability, and alignment with strategic objectives

Control & Risk Assessment

• Identify control gaps and areas of elevated operational risk, including key person dependencies, manual reconciliation points, and exception-handling weaknesses.
• Assess processes against Goldman Sachs' operational risk framework, regulatory requirements, and industry best practices.
• Collaborate with Compliance, Risk, and Technology teams to ensure recommendations align with the firm's risk appetite and regulatory obligations.

Solution Design & Recommendations

• Develop a comprehensive functional roadmap that articulates:
  • Current-state process maps and pain-point analysis
  • Control gap inventory with risk ratings
  • Prioritized recommendations for improvement:
    • AI integration (e.g. AI integration with existing technology stacks, use of firm AI platforms, use of advanced structured prompts)
    • Low-code / no-code automation (e.g., workflow orchestration, ETL, RPA)
    • Strategic technology uplift (e.g., platform migration, API integration, data infrastructure)
    • Behavioural and procedural change (e.g., revised SOPs, training, organizational design adjustments)
    • Measurements (e.g. KRIs, KPIs, dashboards, reporting)
  • Business case estimates including effort, cost, and expected ROI
• Design target-state operating models that improve service, reduce cycle times, and mitigate risk.

Stakeholder Engagement & Change Enablement

• Serve as a trusted advisor to operations leaders, building consensus around modernization priorities.
• Facilitate workshops, interviews, and working sessions with front-office, operations, and technology stakeholders.

Required Qualifications

• Minimum 5 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 in developing and implementing BI 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.

Preferred Qualifications

• 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

Experience Level

Mid Level