Cyber Risk Analytics & Automation Manager

GSK•Philadelphia, PA

About The Position

The Cyber Risk Analytics & Automation Manager serves as the business product owner for cyber risk data, analytics, and automation capabilities used to drive risk-informed decision making across the enterprise. This role is responsible for developing and executing the product strategy and roadmap for cyber risk analytics, ensuring that cybersecurity, technology, and business leaders have clear, actionable insights into risk exposure, control effectiveness, and investment priorities. A core capability of this role is expert storytelling with data—translating complex cyber risk information into compelling narratives, visualizations, and analytical insights that enable stakeholders to understand risk exposure, evaluate trade-offs, and take decisive action. The role will ensure that cyber risk analytics are not simply reports or dashboards, but decision-support products that clearly communicate risk and drive accountability across the organization, including at the executive and Board level. The individual will develop a deep understanding of the user journeys and decision needs of key stakeholder personas—including business leaders, technology leaders, risk owners, and executive leadership—and deliver analytics products that enable data-driven risk treatment decisions, accountability, and board-level assurance. Working at the intersection of cybersecurity, data engineering, analytics, and automation, this role will drive the development of modern analytics platforms and intelligent automation capabilities that transform cyber risk management from static reporting to dynamic decision support.

Requirements

4+ years of professional experience in analytics, data science, cybersecurity, or risk management roles.
Experience designing and delivering analytical decision-support systems or analytics products.
Experience applying product management principles to analytics or data platforms.
Experience working with quantitative models, statistical analysis, and data-driven decision frameworks.

Nice To Haves

Strong background in statistics, quantitative analysis, and data modeling.
Experience with data engineering or large-scale data architectures (data lakes, analytics platforms, or big data environments).
Familiarity with machine learning, generative AI, agentic AI, or intelligent automation technologies.
Ability to translate complex analytical insights into clear, actionable business intelligence and narratives.
Experience in or strong interest in cybersecurity, cyber risk management, or technology risk.
Familiarity with cyber risk frameworks, control environments, and risk measurement concepts.
Demonstrated ability to act as the voice of the customer in prioritizing product capabilities.
Strong track record of driving outcomes through cross-functional collaboration.
Ability to define product strategy, roadmap, and feature prioritization in a complex environment.

Responsibilities

Serve as the product owner for cyber risk data and analytics capabilities, including dashboards, analytical models, automation workflows, and decision-support tools.
Define and maintain the product vision, strategy, and multi-year roadmap for cyber risk analytics aligned with organizational cybersecurity and enterprise risk objectives.
Translate business and cybersecurity needs into analytics product requirements and prioritized feature backlogs.
Develop compelling data-driven narratives and visualizations that translate complex cyber risk information into clear insights for diverse stakeholders.
Ensure analytics outputs enable stakeholders to quickly understand risk exposure, trends, and recommended actions.
Design dashboards, reports, and analytical outputs that support effective storytelling with data for senior leadership and Board-level audiences.
Establish standards and best practices for communicating cyber risk through data visualization, narrative framing, and decision-oriented analytics.
Develop deep understanding of user personas and decision journeys, including: o Business risk owners o Technology leaders o Cybersecurity leadership o Risk and compliance teams o Executive leadership and Board reporting stakeholders
Design analytics products that enable stakeholders to: o Understand cyber risk exposure o Evaluate risk treatment options o Prioritize security investments o Track accountability and risk reduction outcomes.
Partner with data engineering and architecture teams to build scalable cyber risk data platforms and analytics pipelines.
Design and implement quantitative risk analytics, metrics frameworks, and statistical models to support risk measurement and decision-making.
Enable advanced analytics capabilities including: o Predictive risk indicators o Control effectiveness analytics o Investment prioritization models o Scenario and impact analysis.
Identify opportunities to apply automation, machine learning, and generative/agentic AI to improve cyber risk analytics and operational efficiency.
Lead the development of automated workflows, intelligent analytics tools, and decision-support systems that scale risk insights across the organization.
Collaborate with cybersecurity engineering, risk management, GRC, enterprise architecture, and business teams to ensure analytics solutions meet operational needs.
Partner with data science and technology teams to deliver robust, scalable analytics capabilities.
Drive adoption and value realization of cyber risk analytics products across stakeholder groups.
Enable clear, defensible risk reporting and assurance for senior leadership and the Board of Directors.
Translate complex technical risk data into clear narratives and insights that support executive decision-making.