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

About the job

As a Senior Data Scientist, you will play a pivotal role in driving data-driven decision-making and shaping strategic initiatives. Your expertise will directly impact the organisation's ability to understand client behaviour, refine predictive models, and deliver actionable insights that influence key business outcomes.

You will take on the responsibility of developing and optimising machine learning models, analysing complex datasets, and collaborating closely with cross-functional teams to integrate data solutions into broader business strategies! Embedded within a dynamic Data Science team, you will not only contribute technical expertise but also foster innovation and knowledge-sharing, making you an integral part of the company's success. This role offers the opportunity to make a tangible difference and leave a lasting impact on the organisation's growth!

Job Goals

• Design and implement advanced machine learning models to solve complex business problems.
• Optimise the performance of existing models and address weaknesses through detailed analysis.
• Collaborate with cross-functional teams to integrate analytics solutions into business operations.
• Analyse large datasets to uncover patterns, trends, and insights that drive strategic decisions.
• Assist API integrations to ensure seamless functionality and data flow between systems.
• Communicate technical findings effectively to stakeholders through visualisations and clear reports.
• Establish and monitor key performance indicators to measure the impact of data-driven initiatives.

• Proficiency in a programming language such as Python, with experience in using Git for version control.
• Strong SQL skills and familiarity with databases like Redshift, Postgres, or Microsoft SQL Server.
• Solid understanding of machine learning algorithms, concepts, and applications, including regression, K-means, decision trees, neural networks, as well as exposure to generative AI and large language models (LLMs).
• Hands-on experience with cloud platforms such as AWS or Azure.