Our Global SaaS client is now seeking an experienced Data Analyst to join their Global Customer Success Data Science Team for a 10-month contract.
You’ll play a pivotal role in improving how they measure and deliver customer success, driving impact across Customer Experience, Digital Experience, Service Delivery, and Supportability. You will partner closely with cross-functional teams, and ensure that data informs strategy, enhances customer journeys, and scales operational excellence.
Key Responsibilities
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Building robust data foundations: Collaborate with engineering to develop pipelines, improve data integrity, and establish clear metric definitions and governance tailored for international markets.
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Developing actionable dashboards & reporting: Create and maintain scalable, user-friendly dashboards that provide visibility into key performance metrics and think broadly across the end-to-end customer journey.
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Delivering deep-dive analytics: Conduct root cause analysis to uncover drivers of customer pain points, digital adoption challenges, and operational inefficiencies and translate findings into actionable recommendations that improve customer journeys.
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Advancing AI-native analytics: Leverage Gen AI tools to automate recurring insight generation, support AI-powered summarization and anomaly detection, and identify opportunities to replace manual workflows with intelligent automation — helping the team move faster and deliver more scalable, proactive insights.
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Enabling experimentation & continuous improvement: Support A/B testing and digital experience evaluations by analysing performance outcomes and quantifying customer and business impact.
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Influencing strategy through storytelling: Communicate insights and trends clearly and persuasively to technical and non-technical stakeholders, ensuring alignment on decisions that improve customer experience, digital adoption, operational performance, and supportability.
Skills
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8+ years of experience in Data Analytics or Data Science, ideally with exposure to Customer Success, Operations, or Digital Experience domains
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Proficiency in SQL for data extraction, transformation, and pipeline development
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Experience with dashboarding and visualization tools (Tableau, Qlik, or similar)
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Familiarity with big data tools (Snowflake, Databricks, Spark) and ETL processes
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Experience with Python or R for advanced analytics, automation, or experimentation support preferred
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Knowledge of statistical methods and experimentation (A/B testing) preferred
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Machine learning and Generative AI experience is a plus
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A genuine enthusiasm for Gen AI and a growth mindset toward how emerging tools can accelerate analytical work
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Proven ability to communicate analytical findings in clear, actionable narratives for both technical and non-technical audiences
Benefits
