Senior Data Scientist – Consumer Twins

Kantar

Senior Data Scientist developing and deploying machine-learning models for Kantar’s Consumer Twins AI platform. Improving large-scale consumer data systems through analytics, feedback loops and cloud tooling.

Posted 8/7/2026full-timeReading • 🇬🇧 United KingdomSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in developing and deploying machine-learning models, with strong proficiency in Python and experience across the data science lifecycle. Capable of collaborating with cross-functional teams to ensure models deliver real value and improve decision-making.

Highest-signal resume keywords

Machine-Learning Model DevelopmentPython ProgrammingSupervised Learning TechniquesCloud-Based Model DeploymentData Science Lifecycle Management

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Machine-LearningData AnalysisModel DeploymentAnomaly DetectionData Quality ImprovementModel MonitoringData ScienceStatistical AnalysisPredictive ModelingData Visualization

Soft Skills

CollaborationCommunicationOwnershipAccountabilityProblem-Solving

Tools & Technologies

Cloud PlatformsData Science ToolsVersion Control SystemsData Processing FrameworksModel Automation Tools

Industry Keywords

Data ScienceProduction EnvironmentConsumer DatasetsHigh-Traffic PlatformsFeedback Loops

Tech Stack

Tools & technologies

CloudPython

About the role

Key responsibilities & impact

Develop and deploy machine-learning models in production environments
Work end-to-end across the data science lifecycle: problem definition, modelling, deployment and monitoring
Analyse new and existing data sources to improve decision-making and model performance
Design feedback loops that continuously improve outcomes and data quality
Collaborate closely with engineers to deliver scalable, reliable model predictions
Communicate technical insights clearly to non-technical stakeholders
Partner with engineering, operational and commercial teams to take ideas from hypothesis through deployment
Ensure models deliver real value once live

Requirements

What you’ll need

Solid experience working as a data scientist on real-world, production problems
Strong Python skills or a similar language used in applied data science
Experience with supervised learning and unsupervised techniques such as anomaly detection
Exposure to cloud-based model training, deployment and automation
Strong ownership and accountability for data science outputs
Experience with large consumer datasets or high-traffic platforms is advantageous but not essential
Right to work in the United Kingdom; visa sponsorship and relocation support are not available

Benefits

Comp & perks

Flexible hybrid working
25 days leave
2 days paid for volunteering and life event leave
Competitive salary and bonus (bonus dependent on role)
Company pension
Enhanced parental leave
Healthcare options
Wide range of flexible benefits