Product Manager (R-11143) at Dun & Bradstreet (Remote)

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Why We Work at Dun & Bradstreet
We are at a transformational moment in our company journey - and we’re so excited about it. Each day, we are finding new ways to strengthen our award-winning culture, and to accelerate creativity, innovation and growth. Our purpose is to help customers improve business performance with Dun & Bradstreet’s Data Cloud and Live Business Identity, and we’re wildly passionate and committed to this purpose. So, if you’re looking to make an immediate impact at a company that welcomes bold and diverse thinking, come join us!

Want to launch innovative B2B digital products? Looking to lead an integrated team using leading business decisioning data and advanced machine learning algorithm, human-centered design thinking and agile methods? Can you apply creative problem-solving skills to solve complex business challenges?

If so, you may be the next Product Manager to drive the fraud product roadmap for Dun & Bradstreet Finance & Risk Solution team. 

Job Summary:

Dun & Bradstreet’s Finance and Risk Solutions team offers powerful solutions to streamline customers’ finance and operations, manage risk, and enhance business insights. Embed our Dun & Bradstreet Data Cloud through our AI-driven platforms, or API integration directly into customers’ workflows.

As a leading global provider of business decisioning data and analytics, we are designing new products and services, and accelerating delivery through innovative methods and technologies.

Product Managers play a critical role in achieving our strategy. They lead teams of engineers, data scientists, and designers to define product strategy and develop, launch, and enhance products and services that drive our business forward.

We are selectively recruiting for a Product Manager to develop and launch fraud detection Software solutions to help organizations detect and prevent commercial fraud during business, supplier, or merchant account opening, onboarding, and subsequent risk management processes.

Our multi-layer fraud solution approach is built on the proprietary D‑U‑N‑S® Identity Resolution process, combining online and offline business identity and transactional data, and advanced machine learning capabilities powered by unique business consortium data.


  • Build breakthrough experiences and products that solve our users’ most critical fraud prevention needs in a hands-on, collaborative environment with engineers, data scientists and designers
  • Translate product requirements and reported bugs into tickets in Jira
  • Work with engineers during development stage and participate in UAT
  • Participate in agile scrum rituals including sprint planning and daily standup
  • Support pricing, billing, and usage tracking efforts
  • Perform qualitative and quantitative analytics to inform strategy and measure success of product launches
  • Closely work with sales, data science, engineering, fraud operations, and customer support on client demo, proof of concept, contracting, onboarding, and ongoing support efforts
  • Partner with data acquisition, legal, and compliance teams to acquire and onboard new 3rd-party capabilities and data sources for the solution
  • Work with product marketing and sales enablement on go-to-market strategy & tactics, produce collaterals, and knowledge series


  • Entrepreneurial, proactive, and productive - someone who knows how to prioritize what needs to be done and rallies colleagues to get things accomplished; “roll up the sleeves” type of attitude
  • Both insightful and creative, with strong problem-solving skills and pragmatic, with a practical, “real-world” sense of what is actually “do-able”.
  • Possesses an affinity for data-driven insights to make decisions, and able to harness knowledge and expertise of the best content to support the Practice
  • Ability to understand the technical architecture of data products to assess scope and drive timelines
  • Experiences in breaking down problems and making decisions based on data and customer insights


  • Bachelor’s Degree, concentration in a quantitative discipline such as Statistics, Mathematics, Engineering, Computer Science, Econometrics, Business Analytics, or Market Research is preferred
  • At least 2-5 years of technical product management experiences
  • Excellent written and verbal communication skills
  • Highly organized with ability to work with clients with different work styles, tempos, and processes.
  • Ability to self-manage and work both independently and collaboratively.
  • Domain experiences in fraud risk and identity verification (preferred)

Dun & Bradstreet is an Equal Opportunity Employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, creed, sex, age, national origin, citizenship status, disability status, sexual orientation, gender identity or expression, pregnancy, genetic information, protected military and veteran status, ancestry, marital status, medical condition (cancer and genetic characteristics) or any other characteristic protected by law. View the EEO is the Law poster here and its supplement here. 
View the pay transparency policy here.

We are committed to Equal Employment Opportunity and providing reasonable accommodations to qualified candidates and employees. If you are interested in applying for employment with Dun & Bradstreet and need special assistance or an accommodation to use our website or to apply for a position, please send an e-mail with your request to [email protected] Determination on requests for reasonable accommodation are made on a case-by-case basis.

More Information on Dun & Bradstreet
Dun & Bradstreet operates in the Analytics industry. The company is located in Short Hills, NJ, Center Valley, PA and New York, NY. Dun & Bradstreet was founded in 2022. It has 5353 total employees. It offers perks and benefits such as Flexible Spending Account (FSA), Disability Insurance, Dental Benefits, Vision Benefits, Health Insurance Benefits and Life Insurance. To see all 90 open jobs at Dun & Bradstreet, click here.
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