Product Manager – Search Relevance & Retrieval

Bloomberg
New York

About the job

Bloomberg is seeking a Product Manager to lead search indexing, retrieval & ranking for the Bloomberg Terminal. This role is responsible for the core systems that generate search results across semantic search, natural language search, and AI-powered retrieval experiences.

Responsibilities

Define and communicate a clear product strategy for search indexing, retrieval, and ranking

Partner with stakeholders across research, news, and product teams to understand workflows, gather requirements, and prioritize investments

Work closely with evaluation partners to define success metrics, interpret results, and guide decision-making

Translate user needs and business goals into clear product requirements and roadmaps

Drive improvements in search quality, including relevance, coverage, and timeliness of results

Ensure systems support both traditional search experiences and emerging AI-driven workflows

Balance tradeoffs across user impact, performance, and scalability in collaboration with engineering teams

Communicate progress, insights, and outcomes clearly to stakeholders and leadership

Align cross-functional teams around shared goals while maintaining clear ownership of product direction

Qualifications

Minimum

6+ years of product management experience, ideally in search, data products, or ML-powered applications

Strong product sense with the ability to translate complex systems into user-facing value

Experience defining product requirements and working closely with engineering and data science teams

Comfort working with metrics, experimentation, and evaluation frameworks

Proven ability to manage stakeholders and drive alignment across multiple teams

Excellent communication skills, with the ability to clearly articulate strategy and outcomes

Preferred

Experience with search, ranking, or information retrieval systems

Familiarity with evaluation methodologies for search or AI systems

Exposure to LLMs, retrieval-augmented generation (RAG), or question-answering use cases

Experience working with unstructured data (e.g., documents, news, research content)

Background in financial data, enterprise tools, or research workflows