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
Building robust data foundations: Collaborate with engineering to develop pipelines, improve data integrity, and establish clear metric definitions and governance tailored for international markets.
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.
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.
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.
Enabling experimentation & continuous improvement: Support A/B testing and digital experience evaluations by analysing performance outcomes and quantifying customer and business impact.
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
8+ years of experience in Data Analytics or Data Science, ideally with exposure to Customer Success, Operations, or Digital Experience domains
Proficiency in SQL for data extraction, transformation, and pipeline development
Experience with dashboarding and visualization tools (Tableau, Qlik, or similar)
Familiarity with big data tools (Snowflake, Databricks, Spark) and ETL processes
Experience with Python or R for advanced analytics, automation, or experimentation support preferred
Knowledge of statistical methods and experimentation (A/B testing) preferred
Machine learning and Generative AI experience is a plus
A genuine enthusiasm for Gen AI and a growth mindset toward how emerging tools can accelerate analytical work
Proven ability to communicate analytical findings in clear, actionable narratives for both technical and non-technical audiences
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