Product Manager - Quantitative Data Solutions
$140k - $295kBloomberg
Product Manager - Quantitative Data Solutions
Location
New York
Business Area
Product
Ref #
10050467
Description & Requirements
Our research data solutions will 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 normalized and linked historical data products that include company fundamentals, consensus estimates, pricing, supply chain, granular segment level data, macroeconomic and alternative data into an outstanding data solution. We want an ambitious, creative and innovative SME that understands the systematic and quantitative workflow who can help us fashion 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 clients so that they can keep innovating and delivering value to their clients.
Our team is responsible for identifying, creating, and designing data solutions that demonstrate 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 data professional who understands the multiple use cases for research enterprise content including quantitative and quantamental research across multiple investment management strategies.
We will trust you to:
Show domain expertise on research and alternative data, and how investment managers extract signals to build their edge
Stay current on major research trends within the financial industry 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 our Research data content 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
Set, track, and review metrics for desired product outcomes and clearly communicate product vision, roadmap, and development status and complete through collaboration with multiple partners including 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 take on their challenges
Display product management skills and effectively handle 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 big data
Demonstrate strong problem-solving, analytical, and technical skills through proficiency in Python or similar programming languages typically used in data science and data engineering
You will need to have:
A minimum of 5 years'* experience as a Product Manager or related role
A solid understanding of capital markets, preferably in a broad range of asset classes
Familiarity with data science and quantitative investing processes
Basic proficiency in Python, R, or other programming languages typically used in data science, greater proficiency is highly valued
Problem solving skills to deconstruct client problems with a data driven approach when making a case for resources, improvements, and getting management agreement
Self-motivated and driven by innovation and idea sharing
The capability of encouraging relationships with new and existing clients as well building an internal network that champions collaboration and build on a strong culture of teamwork
Bachelor's degree in statistics, mathematics, economics, business management, or other equivalent
Please note we use years of experience as a guide but we certainly will consider applications from all candidates who are able to demonstrate the skills necessary for the role.
Salary Range = 140,000 - 295,000 USD Annual + Benefits + Bonus
The referenced salary range is based on the Company's good faith belief at the time of posting. Actual compensation may vary based on factors such as geographic location, work experience, market conditions, education/training and skill level.
We offer one of the most comprehensive and generous benefits plans available and offer a range of total rewards that may include merit increases, incentive compensation (exempt roles only), paid holidays, paid time off, medical, dental, vision, short and long term disability benefits, 401(k) +match, life insurance, and various wellness programs, among others. The Company does not provide benefits directly to contingent workers/contractors and interns.
Discover what makes Bloomberg unique - watch our for an inside look at our culture, values, and the people behind our success.
Bloomberg is an equal opportunity employer and we value diversity at our company. We do not discriminate on the basis of age, ancestry, color, gender identity or expression, genetic predisposition or carrier status, marital status, national or ethnic origin, race, religion or belief, sex, sexual orientation, sexual and other reproductive health decisions, parental or caring status, physical or mental disability, pregnancy or parental leave, protected veteran status, status as a victim of domestic violence, or any other classification protected by applicable law.
Bloomberg is a disability inclusive employer. Please let us know if you require any reasonable adjustments to be made for the recruitment process. If you would prefer to discuss this confidentially, please email View email address on click.appcast.io
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