Product Manager – Cross Asset Instrument Strategy

Overview

As a Senior Product Manager for cross-asset instrument strategy, you drive the unification of Bloomberg’s instrument system across asset classes within the IPQA scope. You partner with asset-class teams to define a scalable IMS architecture and to align client needs with product delivery. You’ll engage both internal stakeholders and strategic clients to shape the roadmap and ensure value delivery across workflows. This role offers a hands-on chance to influence instrument representation and lifecycle at scale, enabling richer analytics and faster time-to-value.

Responsibilities

• Own and evolve the cross-asset instrument strategy across parallel workstreams
• Drive unification of instrument types within IMS with cross-class collaboration
• Build and sustain relationships with producer teams to align priorities and deliver outcomes
• Advance instrument representation, lifecycle and data modelling in partnership with engineering, quant, and Data Management
• Coordinate multi-team initiatives end-to-end, maintaining momentum and clear delivery
• Engage with strategic buy-side and sell-side clients to translate insights into roadmap priorities
• Monitor market and regulatory developments shaping instrument data requirements

Key requirements

• 10+ years in financial technology, quantitative finance, or related field in a major financial institution or technology provider
• Hands-on experience with financial instruments across at least three asset classes
• Experience driving cross-asset or cross-functional initiatives at scale
• Ability to translate strategic vision into concrete plans and sequences of priorities
• Proven ability to influence senior stakeholders and producer teams without direct authority
• Strong communication skills across technical and business audiences
• Awareness of regulatory landscape and market developments affecting data requirements

• collaboration
• stakeholder influence
• clear communication
• enterprise instrument management systems familiarity
• instrument representation and data modelling
• experience with data-driven or AI-enabled systems

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