Chief Data Officer

SEI•Upper Providence Township, PA

8d•Hybrid

About The Position

SEI is seeking a Chief Data Officer. The CDO will be responsible for driving the growth of recurring revenue streams through innovative data commercialization strategies. In addition, this role will oversee the development and implementation of a cohesive data and artificial intelligence (AI) strategy that unifies efforts across all market units, ensuring alignment with SEI’s broader organizational goals. You will own the commercialization roadmap—assessing market value, packaging data offerings, defining pricing, and driving adoption—while ensuring the foundations (governance-for-monetization, quality, security) are fit for purpose. You’ll partner closely with SEI’s AI leadership to embed intelligence into data products and keep SEI ahead of the market. This role is pivotal to transform data from raw exhaust into customer-grade products that accelerate growth and differentiation. What you will do: Enterprise Data Strategy- Design and execute a robust, long-term enterprise data strategy that aligns with organizational objectives, prioritizing the advancement of actionable, data-informed decision-making throughout every area of the business. Pinpoint critical business domains where data can reveal new opportunities or enhance performance, ensuring the data strategy remains tightly integrated with overarching business goals and priorities. Partner with business leadership to clarify the pivotal decisions the company aims to support using data-driven insights, and develop concrete plans to enable these decisions through targeted data strategy and analytics initiatives. Champion organizational transformation by harnessing data and artificial intelligence to refine processes, boost operational effectiveness, and drive innovation. Collaborate with senior executives to embed the data strategy into wider organizational change efforts. Market & Product Strategy- Define SEI’s data product portfolio: identify high-value datasets, features, and derived insights that solve priority client outcomes across Private Banking & Wealth, Asset Management, and Institutional segments. Align portfolio with SEI’s platform strategy and roadmap. Size the opportunity: lead TAM/SAM/SOM analyses, willingness‑to‑pay research, and competitive scans to quantify market value of SEI’s data assets and inform prioritization. Own the data product lifecycle: from discovery and market validation to launch, pricing changes, packaging, and sunset—treating data as customer-grade products with SLAs, documentation, and support. Monetization & Pricing- Design pricing & packaging: develop value‑based pricing models and discount guardrails by segment and use‑case. Run pricing experiments: establish price ladders, pilots, and monetization experiments to optimize ARR, NRR, and gross margin. Commercial architecture: define contract templates, licensing terms, data rights/usage policies, and revenue recognition in partnership with Finance and Legal—balancing growth with compliance and client trust. Go‑to‑Market & Sales Enablement- Build GTM motions with market units: partner with other units to craft narratives, packaging, and playbooks; enable Sales with demos, ROI calculators, sample feeds, and case studies. Channel strategy: evaluate distribution via APIs, data exchanges/marketplaces, and co‑sell/embedded routes with strategic partners; define trial, freemium, and land‑and‑expand motions. Data & AI Integration- Productize intelligence: embed AI capabilities into data products and to create derived features that increase customer value. Stay ahead on privacy‑preserving tech: shape the adoption of privacy‑enhanced computation, synthetic data, and clean‑room patterns to enable safe, compliant sharing and monetization. Governance‑for‑Monetization- Right‑sized governance: implement pragmatic data governance, quality standards, lineage, and controls tailored to commercial outcomes rather than governance for its own sake. Ethical & regulatory alignment: ensure offerings comply with industry regulations and SEI policies; establish review boards for sensitive use and model‑derived data. Operating Model & Culture- Unify data assets across SEI: break silos and harmonize data domains to increase reuse and platform leverage consistent with SEI’s platform evolution. Build a product‑led data culture: upskill teams on product thinking, pricing, and storytelling; champion “data as a product” practices across technology and business. Outcomes & Metrics- Commit to measurable outcomes: Data ARR and margin, attach rate to existing products, dataset adoption/activation, net revenue retention, cost‑to‑serve, time‑to‑launch, SLA adherence/latency, and client satisfaction (CSAT/NPS) for data products.

Requirements

Proven data product leadership: 10+ years in data product management/commercialization (preferably in financial services), including P&L ownership and taking at least one data product to material ARR/NRR
Pricing expertise: hands‑on experience with value‑based pricing, usage/API metering, enterprise licensing, and price experimentation
Commercial deal‑making: comfort negotiating data licenses, co‑sell agreements, and revenue‑share structures with clients and partners
Platform savvy: familiarity with modern data platforms and distribution patterns, and how to convert platform assets into sellable products
AI + analytics partnership: track record partnering with AI leaders to create data‑plus‑AI offerings and to operationalize feature pipelines and model governance for commercial use
Regulatory & ethical grounding: strong understanding of data privacy, usage rights, and sector regulations; ability to design compliant offerings without stifling innovation
Executive storytelling & influence: exceptional communication; ability to align market units, technology, finance, legal, and sales behind a monetization roadmap

Nice To Haves

Experience selling into wealth/asset management/banking segments; knowledge of AUM‑linked pricing and workflow‑embedded distribution
Familiarity with privacy‑preserving computation and clean‑room architectures for data monetization

Responsibilities

Design and execute a robust, long-term enterprise data strategy that aligns with organizational objectives
Pinpoint critical business domains where data can reveal new opportunities or enhance performance
Partner with business leadership to clarify the pivotal decisions the company aims to support using data-driven insights
Champion organizational transformation by harnessing data and artificial intelligence to refine processes
Collaborate with senior executives to embed the data strategy into wider organizational change efforts
Define SEI’s data product portfolio
Size the opportunity: lead TAM/SAM/SOM analyses, willingness‑to‑pay research, and competitive scans to quantify market value of SEI’s data assets and inform prioritization
Own the data product lifecycle
Design pricing & packaging
Run pricing experiments
Commercial architecture
Build GTM motions with market units
Channel strategy
Productize intelligence
Stay ahead on privacy‑preserving tech
Right‑sized governance
Ethical & regulatory alignment
Unify data assets across SEI
Build a product‑led data culture
Commit to measurable outcomes