Senior Data Scientist – Anti-Fraud & Quality Intelligence

We’re the world’s leading data, insights, and consulting company; we shape the brands of tomorrow by better understanding people everywhere.

Kantar’s Profiles division is home to the world’s largest audience network.

With access to 170m+ people in over 100 global markets, we offer unrivalled global reach with local relevancy. Validated by industry leading anti-fraud technology, Kantar’s Profiles Audience Network delivers the most meaningful data with consistency, accuracy, and accountability – all at speed and scale.

Job Details

Kantar is seeking a highly skilled and motivated Senior Data Scientist to join our global team. This role is central to enhancing the quality and consistency of our 50+ survey panels across 40+ countries. These panels are composed of opted-in, fully consented consumers who provide valuable insights through online surveys. Your mission: to ensure the integrity of our data by detecting and preventing fraudulent activity, and to continuously improve the quality of our panellist pool. 

In recent years, the market research industry has faced increasing threats from online fraud, particularly in incentivised markets. Fraudsters attempt to exploit survey systems for financial gain, and their tactics are constantly evolving. At Kantar, we are committed to staying ahead of these threats by investing in advanced data science solutions and fraud detection technologies. 

This is a high-impact role with the opportunity to collaborate directly with Operational, Commercial, and Data Science leaders. You’ll be part of a talented team of analysts, scientists, engineers, and developers, working on mission-critical systems that support our global research operations. 

What You’ll Do 

• Develop and deploy machine learning models to detect fraudulent panellists and improve panel quality. 

• Contribute to the full data science lifecycle: hypothesis generation, model development, deployment, and monitoring. 

• Analyse new data sources to identify opportunities for model enhancement and decision-making improvements. 

• Design and implement feedback loops to drive better data quality and commercial outcomes. 

• Apply supervised and unsupervised learning techniques to build scalable, production-ready solutions. 

• Collaborate with developers to ensure robust, high-availability of model predictions in a microservices architecture. 

• Create and maintain data pipelines and monitoring tools. 

• Communicate technical insights to non-technical stakeholders, including senior commercial leaders. 

What You’ll Bring 

• 5+ years of experience in data science experience. 

• Experience with supervised learning, unsupervised anomaly detection, or similar quality assurance domains. 

• Strong proficiency with python or a similar language. 

• Proven experience of automating model training pipelines using cloud services. 

• Working experience/knowledge of CI/CD pipelines, IAC and git version control. 

• Excellent problem-solving skills and a collaborative mindset. 

• A strong sense of ownership over data science products. 

• Experience in industries with large consumer marketplaces (e.g. programmatic media, travel, financial services) is a plus. 

• Knowledge or experience with Kafka is a plus. 

Our Tech Stack 

• AWS (Sagemaker, S3, lambda), P