Data Scientist

Il y a 5 heures

Brussels, Brussels, Belgique NTek Software Solutions Temps plein
Job Title: Data Scientist Framework agreements: Download framework agreements Duration: (3 months, full time) Location: Brussels (Hybrid)

Job Description As a data scientist, you will directly participate in the design and development of AI and Data Science solutions to meet the operational and tactical needs of the judicial police. You will be responsible for developing machine learning pipelines, as well as their monitoring and maintenance. You will also be responsible for deploying AI models for the organization, primarily on-premises. You will ensure the implementation of best practices in programming and machine learning within your projects. You will conduct technological monitoring to stay up-to-date with the latest developments in MLOps and machine learning. An awareness of security, ethical, and legal aspects is a plus.

Desired Profile You hold a master's or doctoral degree in computer science, AI, or equivalent and can demonstrate a minimum of 3 years of experience in data science, MLOps, and ML.

You have expertise in the following areas: On-premise and cloud development: Expertise in the development and deployment of AI solutions on-premise and in the cloud (Azure, AWS, GCP). 3+ years of industry experience: You have 3+ years of experience in the world of ML, MLOps and big data with a focus on large-scale deployment. Theoretical background and practical expertise: in the field of ML and deep learning. Database Paradigm (SQL & NoSQL): Advanced knowledge of relational and non-relational databases (SQL and NoSQL), including PostgreSQL, MySQL, Milvus, Neo4j, etc. ML MLOps: Demonstrable experience in deploying ML models and expertise in MLOps. Focus on big data: experience in the exploitation of large structured and unstructured datasets . Containerization and deployment: Experience with Docker and Kubernetes, as well as orchestration tools like Kubeflow. Proficiency with ML pipelines (Kubeflow, MLflow, SageMaker, etc.). CI/CD for ML: Proficiency in implementing CI/CD for ML models and associated code. Data Storage: Experience with different data storage solutions (data lakes, data warehouse houses, object storage (S3)) System architecture: Ability to design an end-to-end ML system taking into account scalability, robustness, maintenance and hardware constraints.

Hard Skill Databases: MySQL, PostgreSQL, Neo4j, Milvus AI Framework: huggingface, mlflow, PyTorch, tensorflow, sklearn, OpenCV, vllm Programming Langages: Python (R est un plus) Orchestration et containerisation: Docker, Kubernetes, Kubeflow Software engineering: uv, ruff, black Cloud Platforms: Azure, AWS Versioning (code et modèles): MlFlow, Git, Github, Gitlab

Languages Language skills: You are proficient in at least English and one of the two national languages (NL/FR).

Soft Skills Ability to unite teams: Ability to align diverse profiles around a common goal. Sense of priorities: Ability to identify critical tasks to achieve objectives, maintain a long-term vision to anticipate next steps, and reorganize work based on unforeseen events or new elements that arise throughout the project. Clear and spontaneous communication: Ability to communicate fluently, convey the right message at the right time and to the right audience. Ability to explain technical concepts to non-technical audiences. Problem-solving and analytical thinking: Ability to approach problems in a structured manner, identify root causes, and propose pragmatic and effective solutions. Ability to step back to evaluate multiple scenarios and choose the solution best suited to the context. Collaboration: Ability to work constructively with all stakeholders, fostering dialogue and the co-creation of solutions. Ability to listen to everyone's needs and constraints to promote a positive and productive work environment. Attention to detail: Ability to pay attention to the technical, functional, and organizational aspects of projects. Ensure code quality, model robustness, deliverable conformity , and adherence to organizational standards. Rigour: Consistently apply best practices and methodologies, document work accurately, and ensure continuous monitoring of project progress while respecting deadlines and quality requirements.

Requirement / Skill Confirmed Data Scientist Azure Docker GIT GitHub Gitlab huggingface kubeflow Kubernetes kite mlflow MySql Neo4J PostgreSQL Python Pytorch ruff Tensorflow