Content Relationship Manager - Alternative Data
Bloomberg
Customer Service
New York, NY, USA
Posted on Mar 25, 2026
Bloomberg runs on data. Our products are powered by information. We combine data and context to give our clients the full picture, around the clock and across the globe. In Data, we are responsible for delivering this data, news, and analytics through innovative technology, at scale, quickly and accurately. We apply problem-solving skills to identify workflow efficiencies and implement technology solutions that enhance our systems, products, and processes.
Our Team
Within Data, our Content Acquisition team partners with third party providers across the world to bring high value datasets to our products and workflows at scale. We are data scouts who are focused on identifying and onboarding datasets that have measurable predictive power for business outcomes such as revenue and other company critical metrics. Data scouting sits at the intersection of business outcomes, market intelligence, vendor partnerships, and dataset evaluation. In partnership with our Product partners, we own the end to end lifecycle for third party datasets, from scouting and market mapping through evaluation, negotiation, onboarding, quality, and ongoing value management.
What’s the Role?
We are looking for an expert Content Relationship Manager to act as a data scout in order to help stand up and scale this initiative for our Alternative Data offerings. You will establish a repeatable, prioritized scouting process that moves us from onboarding one dataset per year to onboarding multiple high impact datasets annually. You will own the vendor and dataset lifecycle from discovery, market mapping, evaluation, signal validation, negotiation, onboarding coordination, and ongoing value and renewal management.
We’ll Trust You To:
- Partner with Product to define priority outcomes, markets, and critical metrics that guide scouting efforts
- Build and maintain market maps across priority categories, including vendor landscape, substitutes, and best in class options of data sets to source
- Define a repeatable evaluation framework with Product, including data quality, feasibility, integration effort, rights, cost, and expected impact
- Partner with Product and Data partners to run signal validation and efficacy testing and document results in a decision ready format
- Drive a structured decision process with documented recommendations, risks, and measurable post launch success metrics
- Own commercial negotiation and contracting strategy, partnering with Legal, Compliance, and Contracts to land the right rights and terms
- Maintain market intelligence on evolving commercial models and competitive benchmarks to strengthen negotiation outcomes
- Lead onboarding plans with Engineering and Data Operations, ensuring delivery method, documentation, metadata, and quality standards are met and remediated quickly
- Implement usage tracking and efficiency measurement routines to improve value from datasets we already have and advise on renewal decisions
You’ll Need To Have:
- 8+ years of experience in alternative data sourcing, data acquisition, market data, or vendor management, ideally in a hedge fund or asset management
- Deep familiarity with the alternative data ecosystem and how to find differentiated datasets
- Strong vendor management and negotiation skills, including renewals and ongoing relationship ownership
- Experience building scalable processes in ambiguous environments and driving cross functional execution
- Strong communication skills and ability to influence across teams such as Product, Quant/Data Science, Engineering, and Legal
- Analytical comfort reviewing sample files, documentation, and quality indicators and partnering with technical teams on signal validation
- Experience using Excel, SQL or Python to support evaluation and usage analysis
We’d Love To See:
- Experience coordinating end to end data sourcing lifecycles, including discovery, evaluation, negotiation, onboarding, data quality, effectiveness tracking, and renewals
- Familiarity with data delivery methods (API, SFTP, cloud) and data catalogs or data dictionaries
- Experience supporting commercialization or adoption of newly onboarded datasets