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Bloomberg Product Manager, Enterprise Data - Systematic/Quant Credit in New York, New York

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 tradingdata and how analysts are utilizing this data to build an edge in thecorporate bond market.

  • Staycurrent on major research trends within the credit markets that continueto evolve and redefine traditional thinking and drive the many use casesfor enterprise data.

  • Develop adeep understanding of our enterprise offering when it comes to creditpricing data content, accessibility, usability, quality, tools, andservices.

  • Set,track, and review metrics for desired product outcomes and clearlycommunicate product vision, roadmap, and development status throughcollaboration with global data specialists, sales, engineers, and supportorganization.

  • Develop apositive relationship with a core group of clients that will partner withus to expand our understanding of their key challenges and evolve ouroffering through ongoing dialogue and experimentation to systematicallyaddress their challenges.

  • Displaystrong product management skills by effectively handling credit dataproduct specification, prioritization, and backlog by continuallyaddressing business needs through an agile process.

  • Understanddata science techniques and platforms that our clients are either buildingor leveraging to extract value from credit pricing data.

  • Train andbe the point of escalation for help desk, sales, and implementation teamsfor credit product capabilities and potential issues, and, when necessary,coordinate internally to address them.

  • Handle thesupport of new and existing clients from a product perspective, ensuringthe credit analytics and workflows are set up to client’s expectations andproviding feedback on client needs, competitor intelligence, and markettrends.

You'll Need to Have:

  • A minimum of 5 years of experience in Quantitative orTechnical Roles

  • 7+ yearsof experience working in financial services, particularly in credittrading or financial technology related to credit markets.

  • Demonstrableunderstanding of quant techniques, particularly related to corporatebonds.

  • Masters orPh.D. degree in a technical discipline (mathematics, finance, physics,engineering, or similar field).

  • Familiaritywith data science and quantitative investing processes.

  • Basicproficiency in Python, R, or other programming languages typically used indata science.

  • Strongproblem-solving, analytical, and technical skills.

We Love to See:

  • Good proficiency in Python or other programminglanguages

  • Self-motivationand a drive for innovation and idea sharing.

  • Thecapability to foster relationships with new and existing clients.

  • Theability to build an internal network that fosters collaboration and buildson a strong culture of teamwork.

  • A solidunderstanding of credit markets, particularly corporate bonds.

  • Problem-solvingskills to deconstruct client problems with a data-driven approach.

  • Thecapability to encourage relationships with new and existing clients.

Salary: 140000,295000,USD,Annual

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