VP, IT Data & Analytics

General Responsibilities

VP- IT Data &

Analytics

The VP of Data & Analytics defines and sets the enterprise strategy and plan to use analytics to advance its business mission and goals. The VP of D&A directs analytics processes, may be responsible for analytics support to other executives and for using analytics to drive innovation and enterprise objectives. In addition, the VP of D&A knows the flow of information, understands its context, and is aware of how it links across the enterprise with regard to deriving value within and for the business. The VP of D&A sets the strategy for enterprise analytics as a business discipline and for using data as an asset to meet enterprise's objectives.

Main Responsibilities

• Collaborate to set policy and standards regarding the use of data and analytics in the organization
• Create mechanisms to use data as a strategic asset throughout the enterprise
• Organize and coordinate the organization's disparate data streams in preparation for analytics and to promote holistic mission-critical analysis
• Innovate and expand the organization's research and analytics offerings
• Oversee the development of analytic metrics that establish a consistent, coherent approach to data throughout the organization to tie analytics into all enterprise functions
• Promote analytic usage and skills among management and employees through programs that training, mentoring, and the selection of appropriate analytics tools
• Provide analytics results directly to business users, allowing them to identify trends and insights;
• Create a culture that promotes data-driven decisions backed by investigation and collaboration around data
• Locate the new and/or best sources for data to drive more effective and efficient analytics
• Measure the ROI of analytics initiatives and create a standard benchmark program for measuring analytics value

Other Responsibilities

• Represent the enterprise to external bodies in the development of industry analytical policies and standards.
• Recruit and develop a data science organization for corporate exploitation of big data and the liberation of dark data, using cloud and social era tools and techniques for data analytics, mining and visualization.
• Create and oversee a centralized service for sourcing external analysis to ensure quality, traceability, timeliness, usability and cost-effectiveness.
• Scan the horizon for emerging analytical skills, techniques, technologies and, where appropriate, tools to ensure their timely introduction for competitive advantage.
• Create and expand analytics based on open data offerings to empower citizens and to enable better government and commercial services.

Reporting Line and Team Structure

• The VP of D&A organizes and builds the analytics organization that consists of analytics leaders, data and information management leaders, technical professionals including, but not limited to:

    ◦ Data scientists

    ◦ Data engineers

    ◦ Business analysts

    ◦ Analytics specialists

    ◦ Report designers

    ◦ Metadata specialists

Organization, Governance and Key Relationships

• The VP of D&A participates in the following governance domains: business strategy and planning, IT and analytics decision-making, data acquisition and use, analytical tools acquisition and methodologies, IT strategy and planning, the ethics of data use, risk and compliance, and marketing strategy and planning.
• The VP of D&A needs to influence and build strategic relationships with the following stakeholders:
• CIO
• Corporate Functions
• Business unit executives —The VP of D&A solicits input, and gains an understanding of the analytics issues and opportunities from each business unit and the key process owners, and integrates their requirements into the development of the enterprise analytics strategy.
• Enterprise data and analytics service providers —The VP of D&A will develop and maintain relationships with key external providers of data and analytical services.

Mandatory Requirements

Job Requirements

Education

A Master's degree in computer science, business analytics, applied mathematics, statistics, engineering, economics, social sciences or related fields is preferred.

Experience

• 15+ years of experience in data and analytics leadership or comparable experience
• Proven track record of working with MDM, big data and social data, as well as cloud-based delivery of solutions
• 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
• Preferably five or more years of experience in digitally advanced enterprises
• Experience in integrating complex, cross-corporate processes and data models,
• Strategy and management consulting experience desirable

Knowledge/Skills

• Leadership and organizational skills and knowledge
• Solid grounding in applied mathematics and statistics
• Keen understanding of business objectives and ability to apply this understanding to recommend and implement product development for difficult and complex technical issues
• Ability to share information across business functions; manage stakeholders with diverse interests; make actionable recommendations
• Excellent analytical, communication, organizational and presentation skills
• Develop solutions which focus on how to successfully extract insight from big data
• Strong, results-driven personality with a high level of enthusiasm, energy and confidence
• Should be passionate and bring expertise in creating a data "discovery-driven" culture
• A background in project management
• Excellent 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
• Strategic technology planning experience; experience in strategic technology planning and execution, and policy development and maintenance
• Ability to effectively drive people, process and technology change in a dynamic and complex operating environment
• Excellent oral and written communication skills, including the ability to explain analytic process concepts and technologies to business leaders, as well as business concepts to technologists;

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