Bloomberg Enterprise Solutions is growing rapidly. At our core, we deliver data that firms use across their enterprise to support capital markets activity. Our customers are engineers, quants and data scientists who leverage our application-ready data covering the entire breadth of the financial markets and our data quality and governance technologies to automate the services they create.

As a Product Manager you will use your knowledge of customers and significant knowledge of clean, linked, tidy and open data to evangelize both internally and externally the benefits and applications of this emerging area. For example, you will intimately understand: best practices for data distribution, quality and governance; automation practices for metadata and schema creation; and how open and linked data principles can be applied across organizations to better manage and query growing volumes of data.

You will work closely with engineers and data scientists to determine the feature roadmap, prototype, and enable sales. You will work closely with sales and marketing to develop CTO, CDO and technologist-oriented presentations and materials discussing open and linked data benefits. You will feel as comfortable writing SPARQL queries linking together 1000s of disparate datasets as they are presenting to hundreds of current and prospective clients at a conference. Most importantly, you will consistently deliver product features that customers find valuable.

We’ll trust you to:

• Identify and understand addressable markets
• Own the vision for the product and bring new product features to market
• Create model prototypes to share with engineering
• Own roadmaps, JIRAs and enablement materials
• Communicate new features to internal and external stakeholders

You’ll need to have:

• Demonstrable experience as a Product Manager
• Experience with large data sets and tools used to manage them
• Code literate in at least one language used by our clients (e.g., Python or R)
• Understanding of knowledge representation and open data
• Some understanding of statistical and Machine Learning techniques
• Experience using Agile and Kanban methods
• Degree in Computer Science, Mathematics or a Quantitative Discipline