Lead Data Analyst, Customer Support
Role Overview
Lead Data Analyst partnering with Customer Support to improve customer outcomes while managing cost to serve and team capacity.
Measure whether channel changes, self-service flows, and AI agents are working for customers.
Own parts of the support metric tree and conduct experiments and causal analyses to establish what changed.
This is an IC3 role.
Key Skills for This Role
Full Job Posting
Salary
- Salary is stated as GBP 75,000–115,000 annually.
Role overview
Lead Data Analyst partnering with Customer Support to improve customer outcomes while managing cost to serve and team capacity.
Measure whether channel changes, self-service flows, and AI agents are working for customers.
Own parts of the support metric tree and conduct experiments and causal analyses to establish what changed.
This is an IC3 role.
What you'll do
- Collaborate with senior Customer Support stakeholders and communicate insights that lead to customer change.
- Own Customer Support metrics such as contact rate, first response, resolution, CSAT, repeat contact, and cost per contact, aligning them with Servicing Cost and Convenience toplines.
- Support target setting and tracking with Operations and Product leaders.
- Measure AI agent, self-service, and deflection impact, including addressable volume, deflection, cost saved, CSAT, repeat contact, and quality.
- Support automation quality calibration and drift monitoring.
- Support WFM capacity planning and forecasting, including demand, staffing models, SLA and wait-time trade-offs, and regional and outsourcing mix.
- Make customer outcome, operational cost, and team capacity trade-offs explicit in channel and staffing recommendations.
- Build and maintain data models and pipelines in SQL and dbt; review colleagues' analytical work.
Qualifications
- Experience with SQL and data pipelines; dbt experience is preferable.
- Confident with complex data models and able to independently design and implement new models.
- Strong quantitative skills; a scientific, technical, analytics, or computing background is ideal.
- Strong communication skills and ability to explain business insights in persuasive, clear analytical narratives.
- Able to structure business problems with minimal supervision and prioritize collaboratively with stakeholders.
- Proactive, takes ownership of customer impact, and follows through beyond analysis.
- Experience with data visualization tools such as Looker, Power BI, or Tableau, and confident data storytelling.
Nice to have
- Customer support, customer experience, or operations analytics experience, including contact demand, WFM, QA, CSAT, or cost to serve.
- Experience applying AI or LLMs to support or analytics workflows.
- Python.
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