V-IT is looking for a Data Scientist for a client in Brussels.

Start: asap
end: end of 2026, renewable
language: English
deadline 27/01

1. DESCRIPTION OF THE TASKS

Following tasks will be performed:

• • Design, implement and optimise advanced AI, NLP, and ML models. Use LLMs, RAG frameworks, and other state-of-the-art approaches.
  • Fine-tune pre-trained models on domain-specific tasks.
  • Conduct thorough research and stay updated on the latest trends and advancements in NLP, ML, and AI technologies.
  • Develop and maintain robust, scalable, and efficient code using Python.
  • Collaborate with cross-functional teams to integrate AI/ML solutions into existing products and services.
  • Perform rigorous analysis and experimentation to improve model accuracy, efficiency, and scalability.
  • Participate in peer reviews and contribute to the continuous improvement of AI solutions.
• • Contribute to the design and implementation of ML application architecture and its solution stack.
  • Develop comprehensive reports and visualisations to communicate insights and findings to stakeholders.

2. KNOWLEDGE AND SKILLS

Following skills and knowledge are required:

• • Experience in Machine Learning and Natural Language Processing.
  • Excellent knowledge of Python and libraries (e.g. Pandas, SpaCy, NLTK, Hugging Face).
  • Experience with deep learning frameworks for complex model architecture such as TensorFlow or PyTorch.
  • Experience with AI-powered code assistants (e.g., Amazon Q, Github Copilot), staying updated with advancements in AI-driven code technologies.
  • Good knowledge of SQL tooling (Oracle, PostgreSQL).
  • Knowledge of NoSQL databases (Elasticsearch, MongoDB).
  • Knowledge of architectural design of scalable ML solutions such as model servers, GPU resource optimisation.
  • Experience with A/B testing and experimental design of ML models.
  • Experience with pre-trained models and LLMs like GPT, and other Transformer-based architectures.
  • Experience with tools like Matplotlib and Seaborn for creating data visualizations.
  • Strong understanding of linguistics and text processing techniques.
  • Proficient in continuous code delivery and unit testing.
  • Understanding of bias in ML applications and bias mitigation techniques.
  • Familiarity with leveraging graph science techniques to solve complex data problems within social networks, knowledge graphs.