Customer Marketing Data Science Specialist

What you’ll do

• End-to-End Analytics Ownership: Lead analytics initiatives from problem definition through to insight delivery and business adoption, ensuring outcomes; not just outputs.
• Business Collaboration & Influence: Partner with Marketing, BI, IS, and other teams to understand challenges, proactively identify opportunities, and shape decisions through data.
• Data Storytelling & Communication: Translate complex analysis into clear, actionable insights; present findings in a way that drives understanding and decision-making across all levels.
• Customer & Marketing Insights: Deliver analysis that informs segmentation, retention, campaign performance, and customer strategy.
• Test-and-Learn Approach: Design experiments, iterate quickly, and continuously improve impact through data-driven learning.
• Technical Execution: Work hands-on across the data lifecycle (data prep, modeling, analysis), applying advanced analytics and ML techniques to real business problems.
• Cross-Functional Delivery: Collaborate effectively across a geographically dispersed team, ensuring alignment, transparency, and progress.

What you bring

• Bachelor’s degree (or equivalent hands-on experience) in Data Science, Statistics, Computer Science, Marketing, Social Sciences, or a related field; certifications in analytics or AI/ML are an asset
• 3+ years of experience in marketing, customer analytics, or data science in a business-facing role
• Proven ability to own analytics projects end-to-end; from problem definition through to insight adoption and measurable business impact
• Strong problem-solving skills with the ability to translate ambiguous business questions into structured analytical approaches
• Proficiency in SAS, Python, R, and/or SQL, with experience working with large, complex datasets
• Experience working with cloud and data platforms such as Azure and Databricks
• Experience with data visualization and BI tools such as Power BI, Tableau, or Looker to communicate insights effectively
• Experience applying predictive modeling, segmentation, experimentation, and/or marketing analytics techniques
• Able to connect technical outputs to clear business insights and strategic recommendations
• Strong communication and storytelling skills; able to present complex ideas in a clear, concise, and actionable way for non-technical audiences
• Comfortable partnering with and influencing stakeholders, with a proactive, curious, and outcome-driven mindset that balances hands-on execution with big-picture thinking