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Ipsos est un groupe d’études de marché et d’opinion qui analyse les comportements, les attentes et les perceptions des consommateurs et des citoyens.

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ipsos.com
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Détails de l’offre

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Description de l’offre

Make Your Mark at Ipsos Are you excited by the potential of generative AI and synthetic data? Do you enjoy applying machine learning to real-world challenges and want to help shape the future of market research? If so, we'd love to hear from you. About the Role Join Ipsos' growing Synthetic Data team and help build the next generation of AI-powered research solutions. Working alongside data scientists, researchers and engineers, you'll explore how synthetic data and digital twins can transform the way insights are generated and delivered.

This is a unique opportunity to work at the cutting edge of generative AI, applying deep learning and LLM technologies to solve genuine business challenges. You'll be involved in designing and evaluating synthetic datasets, building digital twin applications, developing experimentation frameworks and helping turn emerging technologies into practical tools that can be used across Ipsos. You'll have the freedom to test new ideas, learn from experienced colleagues and contribute to innovation that has real commercial impact.

About You

Essential

Skills

Master's degree, PhD or equivalent experience in Statistics, Mathematics, Computer Science or a related discipline.

  • Strong grounding in statistical analysis and machine learning.
  • Proficiency in Python and modern data science libraries.
  • Knowledge of deep generative modelling techniques.
  • Experience working with LLM APIs or open-source LLM frameworks.
  • Understanding of experimental design and model evaluation.
  • Exposure to cloud platforms such as AWS, Azure or Google Cloud.
  • Strong communication and collaboration skills. Desirable

Skills

Experience within market research, analytics or customer insight environments.

  • Familiarity with deploying machine learning models into production.
  • Exposure to advanced generative AI methodologies.
  • Experience contributing to innovation or R&D projects.
  • Proficiency in AI use and adoption to improve efficiency, experimentation and research outcomes. Behaviours
  • Analytical thinking
  • Creative thinking
  • Curiosity and lifelong learning
  • Resilience, flexibility and agility
  • Motivation and self-awareness
  • Empathy and active listening
  • Service orientation and customer service

Benefits

We offer a comprehensive benefits package designed to support you as an individual. Our standard benefits include 25 days annual leave, pension contribution, income protection and life assurance. In addition, there are a range health & wellbeing, financial benefits and professional development opportunities. We have a hybrid approach to work and ask people to be in the office or with clients for 3 days per week. We appreciate you may have commitments outside of work and will consider flexible working applications - please highlight what you are looking for when you make your application.

We are committed to equality, treating people fairly, promoting a positive and inclusive working environment and ensuring we have diversity of people and views. We recognise that this is important for our business success - a more diverse workforce will enable us to better reflect and understand the world we research and ultimately deliver better research and insight to our clients. We are proud to be a member of the Disability Confident scheme, certified as a Level 2 Disability Confident Employer. We provide an inclusive and accessible recruitment process.

Your application will be reviewed by someone from our Talent Team who will be in touch either way to let you know the outcome. Ready to have an impact? Apply now!

Prérequis

  • Master, doctorat ou expérience équivalente en statistiques, mathématiques, informatique ou discipline connexe
  • Solide maîtrise de l’analyse statistique et du machine learning
  • Maîtrise de Python et des bibliothèques modernes de science des données
  • Connaissance des techniques de modélisation générative profonde
  • Expérience des API LLM ou des frameworks LLM open source
  • Compréhension de la conception expérimentale et de l’évaluation des modèles
  • Exposition aux plateformes cloud telles qu’AWS, Azure ou Google Cloud
  • Solides compétences en communication et collaboration

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