Head of Client Data Solutions, MD - Investment Management

Location:
London

Title:
Head of Client Data Solutions, VP3

Role Overview

State Street Investment Management (SSIM) is a global leader in asset management, entrusted with more than $5.5 trillion in assets. For more than three decades, investors worldwide have benefited from our disciplined, precise investment process and powerful global platform offering access to every major asset class, capitalization range and style across the indexing and active spectrums. SSIM is the investment management arm of State Street Corporation, one of the world’s leading providers of financial services to institutions.

Key Responsibilities

• Set and drive the strategy for client data and intelligence across the organization, serving as the bridge between the business and technology, translating corporate objectives into deliverable architecture

• Develop a Client 360 by aggregating data feeds including client hierarchies, holdings, activity, and attribution into a trusted view of the client

• Turn foundation into curated intelligence: sales signals, predicted risks and redemptions, market and wallet share insights, and decision quality outputs

• Define the toolset needed for client intelligence: data science, knowledge graphs, generative interfaces, context engineering, and agentic workflows in partnership with stakeholders

• Establish best practices to democratize intelligence with user considerations: style and format should match the audience for impact, whether:
  Next Best Action tools, high-impact Dashboards or Decision Ready insights or Self-service tools to democratize access to information for accelerated decision making.

• Partner with stakeholders in the business to translate strategic questions into analytical solutions that are shipped, adopted, and used

• Provide input and subject matter expertise into platforms that capture/consume client data (e.g. CRM, Marketing Automation, Client Onboarding, Client Portals, Meeting Intelligence and Data Platforms) and shape roadmaps so they serve the firm's data intelligence needs

• Build and scale a global team of client data product owners data and analytics engineers, analysts, championing a culture of shared success, and establishing a hybrid agent and human capital operating model that lifts the team’s velocity

• Define and track KPIs that measure the value of client data and intelligence—capturing decisions taken from insights, adoption of tools/content, and downstream business impact (e.g., pipeline, flows, retention)—and partner with data owners and stakeholders to deliver and sustain solutions

• Develop AI Engineering skills across the group to take advantage of emerging technologies and accelerate momentum of outcomes

• Demonstrate commercial impact by linking insights to decisions and outcomes—e.g., growth in targeted products invested in, redemptions retained, improved conversion, and decisions changed

• Drive innovative ways of working: AI that knows what users are working on and pushes them what they didn't know they needed; generative interfaces that build themselves around the question; agent fleets that prep, draft, and act

• Ensure strong governance, documentation, and transparency around data definitions, business logic, and methodologies

Qualifications

• 8–15 years in analytics, analytics engineering, BI, or data engineering roles in a large/complex environment, with a track record of delivering client data and intelligence capabilities at scale in asset management

• Domain expertise in the distribution landscape—vendors, gaps, and where the industry’s data infrastructure falls short

• Strong collaboration skills, an ownership mindset, and experience working cross functionally to deliver measurable outcomes

• Experience and judgement to feed into discussions on behalf of the business with other stakeholder groups to know what to build first, what to buy, when to partner, and what to stop, and the ability to defend that view

• Demonstrated experience owning end‑to‑end client analytical products, from data modelling and transformation through dashboards, and stakeholder delivery

• A bias toward incremental delivery, pragmatic outcomes, and removing barriers to ship

• Proven ability to operate with senior…