Head of Data Strategy - Asset Management Operations

JPMorgan Chase & Co.•New York, NY

2d•$175,750 - $260,000

About The Position

As the Head of AM Operations Data Strategy, you will be responsible for defining and executing a comprehensive strategy for the development, governance, and delivery of data across Asset Management Operations, with a particular focus on position, transaction, performance, and attribution data domains. This executive role ensures that data is managed as a strategic asset, supporting business objectives, operational excellence, advanced analytics, and reporting. The role requires deep expertise in fund accounting, investment accounting, and accounting principles to ensure data integrity and compliance across all operational processes. The successful candidate will ensure that data inputs, outputs, and impacts are well understood and optimized for key consumers, including portfolio managers, investment specialists, client service teams, and other operations stakeholders.

Requirements

Bachelor’s degree with demonstrable industry experience in a data-related role, with experience in fund accounting, investment accounting, and accounting principles.
Subject matter expertise in position, transaction, performance, and attribution data domains within an Asset Management ecosystem.
Experience managing delivery across multiple workstreams with varying timelines, priorities, and complexities, especially in accounting, performance, and operations environments.
Demonstrated ability to manage tight delivery timelines and ensure the product and organization are on track to execute and deliver strategic changes that meet goals.
Ability to execute via successful internal partnerships with other organizations, with the ability to influence people at all levels across a broad variety of job functions.
Excellent leadership skills in managing products, programs, projects, and teams.
Structured thinker and effective communicator with excellent written communication skills. Ability to crisply articulate complex technical, performance, and accounting concepts simply to senior audiences with poise and confidence.
Technical understanding of data management and governance, cloud-based data platforms, or data architecture required.
Understanding of product development and Agile methodologies, with experience in product management focused on data products and data-driven decision-making.

Nice To Haves

Strong familiarity with data management tooling (e.g., quality, observability, discovery, profiling).
Experience with regulatory reporting and compliance in Asset Management Operations.
Experience supporting data needs and impacts for portfolio managers, investment specialists, client service, and operations stakeholders.
Strong familiarity with advanced analytics, machine learning, and AI applications in a business context.
Demonstrated experience with cloud-based data platforms and technologies (e.g., AWS, Azure, Google Cloud).

Responsibilities

Drive Data Strategy & Governance: Partner with the AWM Chief Data Officer (CDO) to define target data architecture and maintain the scope and boundaries for the position, transaction, performance, and attribution data domains, ensuring alignment with Asset Management’s data strategy. Collaborate with business process owners and lead data architects in Technology to design scalable, flexible data architecture for these domains, aligned with business needs and accounting requirements.
Own the data landscape for position, transaction, performance, and attribution domains, including migration planning from legacy systems of record (SORs) to strategic SORs.
Identify and govern Critical Data Elements (CDEs) within these domains, supporting regulatory requirements and documenting data consumption and publication to ensure data lineage and compliance with accounting standards.
Own all data domain artifacts (e.g., data dictionary, data quality rules, data lineage documentation) for position, transaction, performance, and attribution data, and manage a team of AM Operations Data Owners to support the creation, maintenance, and enhancement of these artifacts.
Ensure that data management practices for these domains adhere to clearly defined principles, with a robust operating model sustained in partnership with AM Operations leadership.
Manage the governance and evolution of the data domain structure by participating in the Data Architecture Council and making decisions on domain change requests.
Promote data literacy and a data-driven culture within the position, transaction, performance, and attribution data domains and with Product and Operations partners.
Collaborate with other Data Owners to ensure data integration, integrity, and secure access, while enforcing domain boundaries and validating data quality, especially for accounting-related and performance data.
Own and enforce data contracts, ensuring clear agreements of data quality, accessibility, and usage standards between data producers and consumers.
In partnership with AWM-CDO, work with Product Owners to prioritize data initiatives, manage escalations, and define governance frameworks, including the Data Governance Life Cycle (DGLC), to align with business goals and accounting standards.
Develop and articulate the ‘Data Value Proposition’ for position, transaction, performance, and attribution data domains, ensuring alignment with business goals and driving initiatives that maximize value derived from these data assets.
Develop & Enhance Data Products: Lead engagement with data producers and consumers to understand evolving requirements of the user community, with a focus on position, transaction, performance, and attribution data.
Align with reporting, BI, and data science communities to assess needs for these domains, including accounting, regulatory, and performance reporting.
Develop discoverable and reusable data product requirements for transformation and AI/ML use cases, focused on oversight and scale of Operations data domains.
Lead the identification and prioritization of key datasets in these domains, and create roadmaps for data distribution, including enhancements and new products; monitor usage metrics to drive adoption.
Oversee the construction and registration of data products, ensuring accessibility for AI/ML use cases by sourcing, curating, and assembling position, transaction, performance, and attribution data effectively.
Ensure data is described consistently and meets firmwide standards on documentation, vocabularies, interoperability, and accounting principles.
Ensure that data inputs, outputs, and impacts are well understood and optimized for key consumers, including portfolio managers, investment specialists, client service teams, and other operations stakeholders.
Oversee the Mitigation of Data Risks: Oversee data risk metrics through participation in the Data Risk Governance Council and Data Use Council, engaging in discussions and escalation around governance, especially for position, transaction, performance, and attribution data.
Set direction for Product Owners to ensure effective data management within these domains and alignment to execute domain strategies.
Drive Product Owners to execute responsibilities in line with policy expectations for data associated with their domain, including: Uplift of data quality and implementation of business data quality rules, addressing data quality issues, and driving remediation plans. Effective management of data retention and destruction. Ensuring appropriate capabilities are in place to comply with data entitlements and visibility expectations, protecting the security and confidentiality data, and ensuring compliance with relevant regulations and accounting standards.