Product Manager - Enterprise Data

Product Manager - Enterprise Data

Location

London

Business Area

Product

Ref #

• *Description & Requirements**

Enterprise Data at Bloomberg provides machine-readable feeds of news and other unstructured content, as well as AI-powered analytics, including sentiment and more. Text is at the core of what we do today, with audio, imagery, and video increasingly in scope. Our client base includes major hedge funds, asset managers, and investment banks, typically using our feeds and analytics for low latency and intraday trading, market making, quantitative investing, and risk.

Whats the role?

Were looking for a charismatic Product Manager to join a growing team of technologists to help drive and execute on product development across our unstructured datasets. Youll bring with you a few years working in a financial or technology firm in the machine learning/quantitative trading domain, along with some programming and data management skills. Youll work alongside seasoned industry professionals, gaining personal development whilst contributing your strong technical skills and a positive, can-do attitude.

Well trust you to:

Understand client needs, identify improvements and new use cases

Contribute to defining product development plans across text and other unstructured datasets

Drive engineering resources and execute planned development initiatives

Evaluate new unstructured data sources and assess their quality, coverage, and product potential

Create and update portfolios of client-facing technical documentation

Design protocols and tools to facilitate comprehensive product quality checks

Provide quantitative research to support client testing and onboarding

Serve as subject matter expert in client discussions, sales meetings, industry events

Youll need to have:

Bachelors or graduate degree in business, finance, or engineering-related field

5+ years work experience in a financial or technology company

Hands-on experience working with unstructured text data - for example NLP, text analytics, large news or document corpora, or LLM-based pipelines

Knowledge of Python or SQL. Understanding of how ETL pipelines work a plus.

Understanding of data structures, algorithms, machine learning, quantitative trading.

Good written and verbal communication skills.

Sense of humor a plus.

We'd love to see:

Experience with non-text unstructured data: audio or speech, imagery, or video

Familiarity with multimodal machine learning, embeddings, or modern foundation models

Experience building or evaluating data labeling, annotation, or quality pipelines at scale

If indicated, please note that years of experience are a guide; we will consider applications from all candidates who can demonstrate the skills necessary for the role.

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