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Data Science Intern (Jan - Jul 2027)

  • Singapour
  • Singapore
  • On-site
  • Temporary Full-Time
  • Publié le: 21 Août 2026
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Data Science Intern (Jan - Jul 2027)

A propos de l'offre

The Data Science team at Danone Digital Lab Singapore builds AI systems for digital health applications, including computer vision models deployed in consumer-facing products (e.g., growth tracking, rppg, fraility models). 

We are looking for a Deep Learning intern with hands-on experience in training and improving computer vision models, to work directly on production-facing AI systems. 

You will work on improving real-world AI models used in production. 

Typical work includes: 

  • Designing and implementing improvements to computer vision models (e.g., classification, detection, segmentation models) 
  • Running experiments on model architecture, training strategies, and data pipelines 
  • Reviewing and implementing ideas from recent deep learning / CV literature 
  • Defining evaluation metrics and benchmarking model performance 
  • Working with real-world image datasets (noisy, imbalanced, imperfect) 
  • Works independently with minimal supervision and demonstrates strong task management and communication skills 
  • Presenting results and trade-offs to technical and non-technical stakeholders 

A propos de vous

To be successful in this role, you will need…

Required 

  • Strong Python programming skills for machine learning and deep learning workflows. 
  • Hands-on experience developing, training, and evaluating deep learning models using TensorFlow or PyTorch. 
  • Experience with at least one computer vision task such as image classification, object detection, or image segmentation. 
  • Demonstrated ability to conduct experiments, including model architecture selection, hyperparameter tuning, error analysis, and performance evaluation. 
  • Please include a GitHub, portfolio, publication, or project repository showcasing your deep learning work. 

Preferred 

  • Experience working with real-world computer vision challenges, such as data augmentation, class imbalance, noisy labels, limited datasets, or domain adaptation. 
  • Experience with MLOps tooling (e.g., MLflow, Docker, CI/CD, model serving, experiment tracking) and/or deploying models into production environments. 
  • Ability to read research literature and reproduce, adapt, or extend published methods.
  • Experience with modern computer vision architectures (e.g., CNNs, Vision Transformers, U-Net, YOLO). 
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A PROPOS DE DANONE

Flexibility

Do things your way. At Danone Singapore, we believe that our teams work best when they are empowered to work flexibly – this is why our hybrid working policy allows you to agree the right balance of homeworking and office working, in line with yours and the team’s needs.

Focus on development – your way

With a suite of learning opportunities and a strong focus on in-role development, your line manager will work closely with you to help unlock your career ambitions within Danone. Working here you will enjoy a fast-paced, complex environment, which is packed with opportunities for the entrepreneurial spirit. You’ll work with some of the best-known brands in the world, such as evian, Dumex and Aptamil, and we absolutely guarantee that you can just be yourself.

Our values

We live by our core ‘HOPE’ values – H is for Humanism, as people are at the heart of everything we do. O is for Openness, welcoming new ideas from the world we live in. P is for Proximity, as we believe that building close relationships leads to better understanding and trust. E is for Enthusiasm, for those who are as passionate as we are about bringing health through food to as many people as possible.

Diversity and Inclusion is deeply embedded in Danone's DNA, representing our core values and beliefs. We embrace diversity as a driving force for positive change, nurturing an inclusive workplace where every individual is valued.

Join our movement for a healthier world. One Planet One Health BY YOU. For more information about Danone, our divisions and culture, please visit careers.danone.com

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