RedCat Digital
Data Analyst – Customer Success / AI Analytics
Skills
1 month ago
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Important information
Contract type:
Freelance / Contract
Location:
London, UK
Work mode:
Onsite
Published on:
24 September 2026
What they need
Data Analyst – Customer Success / AI Analytics
£285 per day | Inside IR35
Initial 10-month contract
Hybrid – 3 days per week in London, 2 days remote
I’m recruiting for an experienced Data Analyst to join a global Customer Success Data Science team on an initial 10-month contract.
This role is about much more than producing dashboards and reports. You’ll use data to identify business opportunities, influence decisions and deliver measurable improvements across Customer Experience, Digital Experience, Service Delivery and Supportability.
You’ll work across international markets, partnering with technical and business stakeholders while helping develop an increasingly AI-native approach to analytics.
Key responsibilities
- Analyse complex datasets using SQL and Python/R to identify trends, problems and opportunities.
- Build scalable dashboards, reporting and data foundations that enable teams to make better decisions.
- Conduct deep-dive and root-cause analysis into customer, digital and operational performance.
- Translate analysis into clear recommendations that influence business decisions and measurable outcomes.
- Support A/B testing and experimentation, analysing results and quantifying customer and business impact.
- Work closely with engineering teams on data pipelines, ETL, data quality and metric definitions.
- Use Generative AI and automation to improve insight generation, reporting and analytical workflows.
- Manage multiple projects across international markets and adapt to changing priorities.
What we're looking for.
Technical capability
- 8+ years' experience in Data Analytics or Data Science.
- Strong SQL and Python/R skills.
- Experience with dashboarding/visualisation tools such as Tableau, Qlik or similar.
- Exposure to modern data platforms such as Snowflake, Databricks or Spark, plus ETL/data pipelines.
- Experience with experimentation, A/B testing or statistical analysis.
Business impact
- A proven track record of using data to influence a business decision, change an approach or improve a measurable KPI.
- Able to go beyond reporting what happened and explain why it happened, what should be done and the resulting business impact.
Stakeholder communication
- Strong communicator who can turn complex analysis into a clear and compelling story for both technical and non-technical audiences.
- Comfortable engaging directly with stakeholders, challenging assumptions and proactively identifying opportunities.
Ownership & adaptability
- Comfortable working in ambiguous environments and managing multiple priorities.
- Proactive approach, with the ability to take ownership rather than waiting for detailed direction.
- Experience working across different markets or business functions is beneficial.
AI experience
- The team is actively building AI-native analytics capabilities, so we're looking for someone genuinely interested in how AI can improve analytical work.
- Hands-on experience using Gen AI for areas such as automated insight generation, AI-assisted analysis, anomaly detection or intelligent automation would be a strong advantage. Machine learning experience is also beneficial.
- Experience within Customer Success, Operations, Digital Experience, Support or call-centre environments would be particularly relevant.
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