Bloomberg's Enterprise Data business continues to be a market leader when it comes to providing enterprise content for the financial services industry. Our offering includes best-in-class enterprise data, and data delivery via cloud-ready technology. Our committed customer base appreciates the quality of our content, completeness of our coverage, data delivery, technology, tools, and high touch client service model.

Reference Data Team:

The Reference Data product offering is foundational and critical to the success of our Enterprise Content business. We have built a best-in-class data product offering that services client demand for completeness, timeliness and high-quality reference data. The business is core to our Enterprise Data offering with many data categories including, but not limited to, instrument and entity level reference data, terms and conditions, corporate actions, classifications and corporate structure data. Our ambition is to continue servicing the most complex demands and challenges of our clients so that they can keep innovating and delivering value to their clients.

The Role
We are looking for an outstanding Product Manager to define how we make Funds Data content available within the largest financial data marketplace to drive client adoption and evolve the business. You will bring with you a deep understanding of fund market data, trading, operational and end-to end investment cycle workflows. You are curious, creative and passionate of building best-in-class enterprise data products that solves client needs for funds content. You stay current to the latest industry trend and build partnerships with clients to understand their problems and challenges. You will be responsible for documenting our target client challenges and needs, understanding use cases, and then the design, evolution, prioritization and execution of a strategy and product rollout in collaboration with stakeholders. This will include defining product level and overall go-to-market and success metrics.

We will trust you to:

-Define and articulate clear strategies, goals and initiatives that drive predefined and clearly articulated business outcomes

-Display product management skills and effectively lead data product specification, roadmap, prioritization, and backlog by continually addressing business needs through an agile process

-Define and implement the go-to-market strategy to ensure successful data product launches and adoption.

-Partner with Engineering, Support organization and Data operations to ensure deliverables are well understood, and align with the overall business goals

-Develop a positive relationship with a core group of clients that will partner with us to expand our understanding of their key challenges and evolve our offering through ongoing dialogue and experimentation to systematically solve their challenges

-Be the subject matter expert of the enterprise funds products, as well as the accessibility, usability, quality, tools and services available to clients that allow them to deepen their interaction and usage of our content

-Work with Marketing and Sales to promote and attain our desired business outcomes and continuously drive adoption

You'll need to have:

- A minimum of 3 to 5 years experience as an Enterprise Product Manager

- A strong understanding of capital markets and investment management, preferably in a broad range of asset classes

- A deep understanding of public funds across ETF's, Mutual Funds, SMAs and other types including the use case for data including buy side, sell side and fund admins and custodians

- Experience in trading and investment workflows or fund servicing preferred

- Strong relationships with industry associations and/or regulators preferred

- Direct hands on experience working with financial data products and related content from leading financial data providers

- Understand how enterprise clients identify, test, and evaluate financial datasets across vendors before making purchasing decisions and basic concepts of data pipelines including data lakes, data warehouses, ETL, normalization, linkage, etc.

- Proficient with statistics and data science techniques and tools such as Python, R, cloud computing, SQL preferred

- Understand agile principles and have prior experience working with multiple stakeholders to deliver projects and initiatives

- Ability to collaborate in a cross-functional, fast-paced environment