Data Scientist

About the Role: Our client in London is seeking an experienced Data Scientist to support the Case Quality & Evaluation (CQE) team for a 12 month hybrid contract (3 days on site, 2 days remote). In this role, you will leverage data, analytics, and statistical rigor to shape measurement frameworks that improve the global customer support experience. You will collaborate with cross-functional partners - Operations, Engineering, Product, and Data Engineering - to deliver trustworthy measurement, actionable insights, and meaningful business impact. About the Team: The Case Quality & Evaluation (CQE) team enables our client to deliver exceptional customer support by defining, measuring, and optimising key support quality metrics. CQE owns the development of frameworks for customer satisfaction (CSAT), operational quality, and ground-truth labelling. The team partners closely with engineering and product groups to enhance support operations and accelerate AI-powered solutions. Through robust measurement and deep analytical insights, CQE drives improvements in customer experience and operational effectiveness across the company's global support ecosystem. What You’ll Work On (Day-to-Day): Measurement & Modeling • Design, implement, and validate metrics such as CSAT and operational quality to accurately reflect customer support performance. • Develop statistical models and measurement strategies that guide improvements in support quality and customer experience. Data Quality, Coverage & Labeling • Build and refine sampling methodologies and validation processes. • Ensure pipeline accuracy, data integrity, and comprehensive measurement coverage across all support channels. • Support ground-truth creation through expert labelling processes and quality frameworks. Cross-Functional Collaboration • Partner with quality & evaluation teams, product managers, engineers, and operations to define success metrics and understand the impact of new features and workflows. • Ensure measurement infrastructure is scalable, reliable, and integrated into reporting and dashboard systems. Insight Generation & Continuous Improvement • Analyse large, complex datasets to surface trends, insights, and recommendations. • Communicate findings to technical and non-technical stakeholders. • Continuously optimise measurement tools, frameworks, and processes. Key Projects You’ll Support • Defining and refining success metrics with product managers. • Assessing the impact of product feature launches on support quality. • Driving insights for high-touch support improvement initiatives Minimum Requirements: • 5+ years of experience in Data Science or a similar analytical role. • Strong proficiency in Python, R, SQL, and modern data analysis tools. • Demonstrated experience working closely with product teams and contributing to product decision-making. • Expertise in statistical analysis, modeling, and data visualisation. • Ability to translate complex analyses into clear, actionable insights for stakeholders. • Bachelor’s degree or higher in Computer Science, Statistics, Mathematics, or a related field. Preferred Qualifications: • Strong collaboration and stakeholder-influencing skills. • Experience transforming data insights into product strategy inputs. • Data engineering familiarity (pipelines, ETL, data validation). • Previous experience in support operations or integrity environments. Benefits: • Competitive salary • Healthcare contribution and inclusion in company pension scheme • Work laptop and phone • 25 days annual leave (pro-rata) plus paid bank holidays • Expanding workforce with potential for career progression for top performers