Why We Work at Dun & Bradstreet
Dun & Bradstreet combines global data and local expertise to help clients make smarter decisions. With 6,000+ people in 31 countries, we are a team of diverse thinkers and problem solvers who all share a common curiosity: to find new ways to turn data into value. If you share this curiosity and want to be part of a future-ready company, come join us! Learn more at dnb.com/careers.
About the role
Join Dun & Bradstreet's Marketing Analytics team, where you'll provide data-driven insights that fuel targeting, segmentation, and resource prioritization. Powered by the world's largest B2B data source, we're at the heart of data-driven marketing.
Your duties
Analytics Partner: Collaborate with marketing and sales teams to drive upsell, cross-sell, and new customer acquisition campaigns through segmentation and modeling.
Predictive Insights: Deliver predictive analytics to support customer retention campaigns.
Storytelling: Turn data into compelling stories that influence decision-making and automate analytical processes
Responsibilities:
Strategic Partnerships: Collaborate with marketing and sales teams to set priorities and drive impactful business outcomes.
Machine Learning Models: Work with models for upsell, cross-sell, and new customer acquisition campaigns.
Predictive Analytics: Leverage product usage data to create models that predict customer retention.
Value Analytics: Develop benchmarks for customer lifetime value and spending.
Impact Measurement: Assess the effectiveness of targeting and segmentation strategies.
Thought Leadership: Continuously improve processes, focusing on scaling and automation.
Data Enhancement: Drive improvements in existing data sources and predictive analytics.
Insight Visualization: Transform key insights into compelling stories that influence business decisions.
Skills:
Experience: Minimum of three years in analytical roles.
Influencing Skills: Proven ability to influence senior leaders across multiple functions.
Communication: Excellent written and verbal communication skills.
Programming: Advanced skills in R, Python, or Julia.
Machine Learning: Expertise in classification and clustering algorithms.
Data Handling: Ability to query and manipulate large datasets.
Dashboard Skills: Advanced skills in building Tableau or Power BI dashboards.
Education: Bachelor's degree in Business Management, Mathematics, Statistics, Computer Science, or a related quantitative field preferred.
