Senior Data Scientist – Production ML for Consumer Twins

Kantar Group Limited; Reading; Hybrid; GBP 90,000 - 120,000; Full time

Benefits offered by this job

Flexible hybrid working

25 days leave

2 days volunteering and life event le​

Competitive salary and bonus

Company pension

Enhanced parental leave

Healthcare options

Wide range of flexible benefits

Job summary

Kantar Group Limited is seeking a Senior Data Scientist to work on the Consumer Twins platform in Reading. You will build and deploy machine‑learning models in production, collaborating with engineering, analytics and commercial teams to ensure real‑world value from live systems.

You will own end‑to‑end lifecycle activities, from problem framing to monitoring, with a focus on data quality, model performance and scalable predictions.

Qualifications

• Solid experience as a data scientist solving real‑world production problems.
• Strong Python skills (or equivalent language used in applied data science).
• Experience with supervised and unsupervised techniques (e.g., anomaly detection).
• Exposure to cloud‑based model training, deployment and automation.

Responsibilities

• Developing and deploying machine‑learning models in production environments.
• Work end‑to‑end across the data science lifecycle: problem definition, modelling, deployment and monitoring.
• Analyze data sources to improve decision‑making and model performance.
• Design feedback loops to improve outcomes and data quality.
• Collaborate with engineers to deliver scalable, reliable model predictions.
• Communicate technical insights clearly to non‑technical stakeholders.

Skills

Production ML

Python

Supervised learning

Unsupervised learning

Cloud deployment

Ownership & accountability

Tools

AWS

Azure

Job description

Kantar Group Limited is seeking a Senior Data Scientist to work on the Consumer Twins platform in Reading. You will build and deploy machine‑learning models in production, collaborating with engineering, analytics and commercial teams to ensure real‑world value from live systems.

You will own end‑to‑end lifecycle activities, from problem framing to monitoring, with a focus on data quality, model performance and scalable predictions.