Data Scientist

Mackin Talent; City Of London; Hybrid; GBP 50,000 - 70,000; Full time

Job summary

A recruitment agency seeks an experienced Data Scientist in London for a 12-month hybrid contract. In this role, you will employ data analytics and statistical rigor to shape frameworks that improve customer support quality. The ideal candidate will have over 5 years of experience and proficiency in Python, R, and SQL, alongside strong collaboration skills. Join a dynamic team focused on enhancing customer experience through data-driven insights, while enjoying a hybrid working setup.

Benefits

Healthcare contribution

Company pension scheme

Work laptop and phone

25 days annual leave plus paid bank holidays

Career progression potential

Qualifications

• 5+ years of experience in Data Science or a similar analytical role.
• Strong proficiency in relevant programming languages and tools.
• Expertise in statistical analysis, modeling, and data visualization.

Responsibilities

• Design and validate metrics to reflect customer support performance.
• Develop models and strategies to improve support quality.
• Build sampling methodologies and ensure data integrity.
• Partner with teams to define success metrics.
• Analyze datasets to provide insights.

Skills

Python

R

SQL

Statistical analysis

Data visualization

Collaboration skills

Education

Bachelor’s degree or higher in Computer Science, Statistics, Mathematics, or a related field

Tools

Modern data analysis tools

Job description

London, United Kingdom | Posted on 11/20/2025

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 optimizing key support quality metrics. CQE owns the development of frameworks for customer satisfaction (CSAT), operational quality, and ground‑truth labeling. 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 labeling 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.
• Analyze large, complex datasets to surface trends, insights, and recommendations.
• Communicate findings to technical and non‑technical stakeholders.
• Continuously optimize 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.

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 visualization.
• 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.
• Previous experience in support operations or integrity environments.
• 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.