Data Scientist, Marketing Analytics

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.