About Us:

Bloomberg’s Enterprise Data business continues to be a market leader in providing enterprise content for the financial services industry. Our offering includes outstanding enterprise data and data delivery via a fully managed platform. Our committed customer base appreciates the quality of our content, completeness of our coverage, data delivery, technology, tools, and high-touch client service model.

Our Research Data Solutions deliver the most compelling, innovative, and comprehensive point-in-time data solution for quantitative and quantamental analysis in the capital markets industry. We are producing a suite of pre-processed and linked historical data products that include company fundamentals, estimates, pricing, supply chain, granular segment-level data, macroeconomic and alternative data into outstanding data solutions. We want an ambitious, creative, and innovative SME who understands systematic and quantitative investment workflows to help us shape this portfolio of products into something truly outstanding that will help us achieve our goal of becoming the industry leader in this space.

This business is core to our growth strategy across Enterprise Data, and our ambition is to continue servicing the most complex demands and challenges of our investment research and trading clients. Our team is responsible for identifying, creating, and designing data solutions that leverage Bloomberg’s proprietary analytics and industry-leading research data. This requires an in-depth understanding of a research analyst’s workflow. Key to this is understanding the multifaceted challenges our clients are trying to solve and making sure that we remain their trusted partner as they work with us to build solutions driven by outstanding data.

We are looking for an experienced product manager or research analyst who understands the multiple use cases for research content, including quantitative and quantamental techniques , with a particular focus on Systematic Credit.

We'll Trust You To:

Show domain expertise on credit pricing and trading data and how analysts are utilizing this data to build an edge in the corporate bond market. Stay current on major research trends within the credit markets that continue to evolve and redefine traditional thinking and drive the many use cases for enterprise data. Develop a deep understanding of our enterprise offering when it comes to credit pricing data content, accessibility, usability, quality, tools, and services. Set, track, and review metrics for desired product outcomes and clearly communicate product vision, roadmap, and development status through collaboration with global data specialists, sales, engineers, and support organization. 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 address their challenges. Display strong product management skills by effectively handling credit data product specification, prioritization, and backlog by continually addressing business needs through an agile process. Understand data science techniques and platforms that our clients are either building or leveraging to extract value from credit pricing data. Train and be the point of escalation for help desk, sales, and implementation teams for credit product capabilities and potential issues, and, when necessary, coordinate internally to address them. Handle the support of new and existing clients from a product perspective, ensuring the credit analytics and workflows are set up to client’s expectations and providing feedback on client needs, competitor intelligence, and market trends.

You'll Need to Have:

A minimum of 5 years of experience in Quantitative or Technical Roles 7+ years of experience working in financial services, particularly in credit trading or financial technology related to credit markets. Demonstrable understanding of quant techniques, particularly related to corporate bonds. Masters or Ph.D. degree in a technical discipline (mathematics, finance, physics, engineering, or similar field). Familiarity with data science and quantitative investing processes. Basic proficiency in Python, R, or other programming languages typically used in data science. Strong problem-solving, analytical, and technical skills.

We Love to See:

Good proficiency in Python or other programming languages Self-motivation and a drive for innovation and idea sharing. The capability to foster relationships with new and existing clients. The ability to build an internal network that fosters collaboration and builds on a strong culture of teamwork. A solid understanding of credit markets, particularly corporate bonds. Problem-solving skills to deconstruct client problems with a data-driven approach. The capability to encourage relationships with new and existing clients.