The VP, Chief Data Officer is the senior executive who bears responsibility on behalf of an enterprise to foster value creation from the use of the organization's data assets, as well as the external data ecosystem. The authorities include value creation through data exploitation, envisioning data-enabled strategies as well as enabling all forms of business outcomes through analytics, data and analytics governance, and enterprise information policy. This role is the head of all enterprise analytics, decision making affecting analytics, directing analytics processes, and for using analytics to drive innovation and enterprise objectives. Moreover, the VP, Chief Data Officer is the senior-most executive with responsibility for aligning data policy and administration with relevant regulatory, legal and ethical mandates.
• Be the executive with authority, responsibility and accountability to exploit the value of enterprise information assets and the analytics used to render insights for decision making and regulatory reporting.
• Define information strategy practices, lead the creation and assure the ongoing relevance of the firm's information strategy in association with the CIO, chief business officer, chief strategy officer and CEO.
• Drive the development and deployment of the enterprise's data and analytics platform for knowledge management.
• Work with the Customer Group EVPs, CBO, the CIO, other C-level executives and legal to establish vision, to govern and to create a culture that manages data as an enterprise asset.
• Identify and standardize the use and governance of data and analytics in support of the enterprise's business strategy. This includes the governance of data and algorithms used for analysis, analytical applications and automated decision making.
• Institute a programmatic approach for enterprise information management to identify, prioritize and execute the data and analytic initiatives with clear line of sight to enterprise strategies and business outcomes.
• Be the corporate leader of data-driven insights that help support exploitation of strategic and tactical business opportunities, and be a champion for a data-driven, decision-making culture.
• Exploit data using research and analytics to maximize the return on data assets, and develop methods to ensure consistent application and use of analytics.
• Innovate with and expand the organization's research and analytics offerings — emerging analytical approaches, skills and technologies.
• Identify new kinds, types and sources of data to drive business innovation throughout the organization. Define processes for the effective, integrated introduction of new data.
• Be a marketing champion for the information services provided by the enterprise and related data and analytics management capabilities.
Regulatory and Governance Accountabilities:
• Lead regulatory and compliance programs related to data and analytics assets.
- Ensure that appropriate audit controls exist for data and analytics that serve as the source material for regulatory reports.
- Ensure that the data used for financial reporting and to support legal requirements is valid, reliable, traceable, timely, available, secure and consistent.
- Develop and maintain controls on data quality, interoperability and sources to effectively manage corporate risk associated with the use of data and analytics.
- Create policies and controls for the appropriate protection of enterprise information assets through a defined life cycle, from acquisition or creation to end of life destruction and disposal procedures.
• Organize and lead a data and analytics governance council to provide executive sponsorship and oversight for governance policy creation and compliance.
• Organize and chair a data and analytics governance council that meets at least quarterly. Participants typically include CFO, CIO, CHRO, head of risk, CISO, head of enterprise architecture and leaders representing a number of key business units, and legal (often acting in the role of local data stewards).
• Participate in the following governance domains: business strategy and planning, management and financial reporting, enterprise architecture, IT strategy and planning, risk and compliance, and marketing strategy and planning. This includes participating in other governance forums where the VP, Chief Data Officer input is desired.
• Define, manage and advance enterprise information management principles, policies and programs for stewardship and custodianship of data and analytics, in concert with legal, information security, and corporate risk and compliance offices.
• Evolve and institutionalize behaviors for the appropriate use of information within changing security requirements, privacy needs, ethical values, societal expectations and cultural norms.
• Define, manage and ensure an adequate information trust model, controls for master data and metadata management, including reference data.
• Ensure that business reports derived from controlled data are consistent and representative of the true state of the business.
• Ensure the performance of independent audits, as appropriate.
Management and Operational Accountabilities:
• Develop, manage and control the annual budget for the office of the VP, Chief Data Officer.
• Organize and lead a data and analytics center of excellence. Define member responsibilities and accountabilities for both. Define job roles, recruit candidates and then manage directly or indirectly a team of data and analytics governance leaders and senior information management professionals.
• Develop the enterprise's capacity to develop insights with advanced analytics. Recruit and develop data science competencies and resources for the corporate exploitation of big data and sourced data as well as the liberation of dark data, using a combination of open source, cloud and social era tools and techniques for data analytics, machine learning, mining and visualization.
• Lead the development, publication and maintenance of the corporate information architecture, as well as a roadmap for its future development that matches and supports business needs.
• Measure master data and reference data for compliance to policy, standards and conceptual models. Assure the deployment and management of data quality monitoring practices.
• With the IT team, oversee the integration and staging of data, and the development and maintenance of the data lakes, data warehouse and data marts, for use by analysts throughout the organization.
• Facilitate the evolution to self-service analytics and data preparation.
The VP, Chief Data Officer has an organization consisting of data and analytics leaders, technical professionals, and other specialists who may include the following, either as direct reports or matrix team members:
• Program Mgmt
• Information strategists
• Information stewards
• Data engineers
• Data curators
• Information and/or data architects
• Data modelers
• Master data management (MDM) program manager(s) and specialists
• Metadata specialists, taxonomists and ontologists
• Records managers
• Content management specialists
• Risk and regulatory compliance specialists
• Data sourcing managers
• Business process analysts
• Report designers
• Business analysts (data, analytics and/or applications)
• Analytics specialists
• Data scientists
• Algorithmic business domain experts
• Information product managers
A bachelor's or master's degree in business administration, computer science, data science, information science or related field, or equivalent work experience. Academic qualification or professional training and experience in legal and regulatory areas are also desirable.
• Fifteen or more years of business experience, ideally in business management, legal, financial or information or IT management — recently at or near the executive level.
• Five or more years of progressive leadership experience in leading cross-functional teams and enterprise wide programs, operating and influencing effectively across the organization and within complex contexts.
• Experience in integrating complex, cross-corporate processes and information strategies, and/or designing strategic metrics and scorecards.
• Strategy and management consulting experience desirable.
• Excellent business acumen and interpersonal skills; able to work across business lines at senior levels to influence and effect change to achieve common goals.
• Demonstrated leadership; proven track record of leading complex, multidisciplinary talent teams in new endeavors and delivering solutions.
• Proven data literacy — the ability to describe business use cases/outcomes, data sources and management concepts, and analytical approaches/options. The ability to translate among the languages used by executive, business, IT and quant stakeholders.
• Information strategy experience; experience in strategic technology planning and execution, and policy development and maintenance.
• Analytical skills: outstanding analytical and problem-solving abilities.
• Familiarity with business information generation and analysis methods.
• Ability to effectively drive business, culture and technology change in a dynamic and complex operating environment.
• Gravitas to develop a framework for information and analytics governance, as well as to sell and embed it in all levels of the business.
• Excellent oral and written communication skills, including the ability to explain digital concepts and technologies to business leaders, as well as business concepts to technologists; the ability to sell ideas and process internally at all levels, including the board and investors.
• Proven record of effective leadership, including the ability to balance team and individual responsibilities; building teams and consensus; getting things done through others not directly under his/her supervision; working ethically and with integrity.
• Demonstrated knowledge of data structure desired, but not essential; information systems/tools, and related software and data management; enterprise content management, and record-keeping policies and practices in a complex organizational environment.
• Broad experience desired, but not essential, in multiple domain areas, such as data warehousing, business intelligence (BI), data governance, data architecture, data integration, data classification, data strategy, data quality management, data security and privacy, MDM, data standards, regulatory compliance, and enterprise architecture frameworks.