Data & Decision Intelligence, Information Security Manager

BNY Mellon•Pittsburgh, PA

22h•$120,000 - $218,000•Hybrid

About The Position

BNY Mellon is a leading global financial services company at the heart of the global financial system, influencing nearly 20% of the world’s investible assets. The company leverages cutting-edge AI and breakthrough technologies to collaborate with clients, driving transformative solutions. This role is for a Senior Vice President – Data & Decision Intelligence within the Network & Cloud Security Organization. It is a founding role for the function, reporting to the Senior Director, Strategy & Innovation. The role is located in Pittsburgh, PA or Lake Mary, FL, with a hybrid work arrangement. The primary objective of this role is to produce tangible outcomes such as better executive decisions, quantified risk reduction, and measurable value realization from the network and cybersecurity investment portfolio. Operating within the Strategy & Innovation function’s value-realization mandate, this role is an accountable, AI-leveraged capability. A single senior owner, amplified by AI and analytics tooling, will deliver the insight typically provided by a full analytics team, and will be accountable for the decisions leadership takes based on this evidence. The role is expected to demonstrate value early and scale only on demonstrated results.

Requirements

Bachelor’s degree in a quantitative, engineering, or computer science discipline – data science, statistics, computer science, engineering, information systems, or a related field; advanced technical degree preferred.
12+ years of experience in data and analytics, decision science, technology strategy, or infrastructure and security analytics, including a demonstrable track record of turning complex technical data into executive decisions and measurable value.
Deep hands-on expertise in data analysis and decision intelligence: defining metrics and outcome measures, building baselines, correlation and trend analysis, and quantifying risk, value, and outcome attribution.
Strong working knowledge of network and cybersecurity domains and their telemetry and data sources – configuration and asset data, network telemetry, security findings, automation activity, control evidence, and service and adoption data – sufficient to interpret evidence across domains.
Demonstrated ability to establish common definitions, baselines, data lineage, and confidence levels, and to identify and escalate data-quality gaps across distributed source systems.
Proficiency with modern data and analytics tooling, including SQL, Python or equivalent, data visualization, and analytics platforms, with the ability to produce reproducible, auditable analysis with documented assumptions and versioning.
Practical experience applying AI-enabled and agentic analysis to scale insight, with sound judgment on confidence, verification, and human accountability.
Comfortable operating with ambiguity and shaping structure where none yet exists, paired with excellent executive communication skills — able to translate technical evidence into clear recommendations, options, tradeoffs, and confidence levels that drive senior-leadership decisions.
A track record of influencing across architecture, engineering, security, operations, finance, and vendor-management stakeholders as an authoritative interpreter of their data, and driving decisions to conclusion without assuming ownership of their platforms or their delivery.

Nice To Haves

advanced technical degree preferred

Responsibilities

Turn network, cybersecurity, automation, operational, financial, and service data into executive decisions — defining the questions leadership needs answered and delivering clear recommendations, options, tradeoffs, and confidence levels.
Give leadership a single, recurring answer to “are we measurably more automated, resilient, secure, and consumable than last period?” through a North Star progression view, and identify the specific decisions and interventions that answer should trigger.
Quantify whether specific investments reduced cyber and operational risk and produced the intended capability — attributing outcomes to investments and surfacing where spend can be consolidated, redirected, or stopped.
Produce the capability and vendor intelligence that drives renewal, consolidation, and prioritization decisions with a security and value lens — translating analysis into actionable cost and risk outcomes.
Act as the accountable interpreter of authoritative data — configuration and asset data, network telemetry, security findings, automation activity, control evidence, service performance, and vendor and financial information — validating and stress-testing evidence rather than owning the production data platforms.
Establish common definitions, baselines, data lineage, and explicit confidence levels so every conclusion is transparent and defensible, and escalate data-quality and ownership gaps to accountable source and platform teams.
Supply the measured evidence that leadership uses to keep execution aligned to strategy — outcome confidence, dependency impact, and early signals where results are drifting from intent — so leadership can intervene before value is lost.
Apply AI-enabled and agentic analysis to accelerate insight and scale output, exercising sound judgment on confidence, verification, and where a human decision and human accountability are required.
Partner with Architecture, Engineering, Automation, AIOps and data-platform, Security, Finance, and Sourcing teams to source authoritative evidence and drive decisions to conclusion, while respecting their platform and delivery accountabilities.