Senior Customer Analyst Data and AI
Employment Info
JOB SUMMARY
Requirements
- A tertiary qualification in Mathematics, Statistics, Economics, Computer Science, Analytics, or a related quantitative field is required.
- At least 5 years of hands-on analytics experience, including significant exposure to customer, marketing, or loyalty analytics environments, is required.
- Exceptional SQL skills for writing and optimizing complex queries are required.
- Experience building data transformation models using DBT and Google BigQuery is required.
- Proficiency in Python or R for exploratory data modeling, statistical testing, and uplift analytics is required.
- Experience designing target/control methodologies, incrementality analysis, and measurement frameworks for loyalty and CRM campaigns is required.
- Advanced proficiency in Tableau for executive-ready dashboards and data storytelling is required.
- The ability to drive complex workstreams independently, navigate ambiguity, and deliver high-quality outputs with minimal supervision is required.
- The ability to evaluate trade-offs between delivery speed and analytical depth and identify long-term opportunities for analytics adoption is required.
- A demonstrated commitment to team growth through mentoring peers, sharing knowledge, and fostering constructive feedback is required.
Responsibilities
- Lead the complete customer analytics lifecycle across concurrent workstreams, from framing ambiguous business problems through target/control setup, execution, measurement, and stakeholder delivery.
- Translate complex campaign outcomes, loyalty metrics, and customer behavior patterns into clear narratives, recommended actions, and quantifiable business opportunities.
- Design and own statistically sound test-and-learn frameworks, target/control group methodologies, incrementality models, and uplift measurement for marketing campaigns and loyalty streams.
- Build and maintain production-grade data models on Google Cloud Platform using BigQuery, DBT, and Python or R, replacing manual workflows with scalable automated datasets.
- Establish trusted advisor relationships with Marketing, Commercial, and Loyalty stakeholders and partner with Product Managers and Data Leads to shape squad roadmaps and influence business decisions.
- Create data lineage assets, standard operating procedures, and accessible documentation, and contribute to D&AI chapter standards and peer review loops.
- Coach and mentor mid-level, junior, and graduate analysts and conduct code and peer reviews to elevate team capability.
Desired Qualifications
- Understanding of marketing activation platforms and pipelines such as Responsys and Salesforce Marketing Cloud.
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