ICT Advisor – Data Scientist – ML Engineer

Federal Police – General Judicial Directorate

Work Environment

The Federal Judicial Police is a specialized police force, mainly responsible for combating organized crime in all its forms. It is one of the three general directorates of the federal police and focuses on investigative cases related to areas such as cybercrime, terrorism, organized crime, drug trafficking, and many others. It provides support and expertise to the entire integrated police force, as well as to its national and international partners.

Within this directorate, operational resources are assigned to judicial police operations, the fight against serious and organized crime, special units, as well as technical and scientific police operations.

This function includes two complementary aspects: on the one hand, coordinating AI and Data Science projects, and on the other, providing technical expertise in implementing solutions.

Regarding coordination, you will be the reference person within the organization for the implementation of AI initiatives. You will collaborate closely and regularly with other IT and business profiles in the organization to translate operational needs into viable projects. In this context, you will also assume the technical lead on the AI and Data Science aspects of the projects you participate in, overseeing all phases of the projects: analysis, development, industrialization, monitoring, and maintenance. You will also supervise junior and medior technical profiles involved in projects under your responsibility, without systematically taking on the role of project manager.

On the implementation side, 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. As a senior member, you will ensure the implementation of best practices in programming and machine learning within the team. You will conduct technological watch to stay up to date with the latest developments in MLOps and machine learning, and be able to advise your colleagues in their technological and programming choices.

Required Profile

You hold a master's or a doctorate in computer science, AI or equivalent, and can demonstrate at least 5 years of experience in the fields of data science, MLOps, and ML.

You have expertise in the following areas:

• On-premise and cloud development: Expertise in developing and deploying AI solutions on-premise and on the cloud (Azure, AWS, GCP).
• 5+ years of industry experience: You have 4+ years of experience in the field of ML, MLOps, and big data.
• Theoretical background and practical expertise: in ML and deep learning.
• Database Paradigm (SQL & NoSQL): Strong knowledge of relational and non-relational DBs (SQL and NoSQL), including PostGres, Mysql, Milvus, Neo4J, etc.
• ML MLOps: Demonstrable experience in deploying ML models and expertise in MLOps.
• Big data focus: Experience in exploiting large structured and unstructured datasets.
• Containerization and deployment: Experience with Docker and Kubernetes as well as orchestration tools such as Kubeflow. Proficiency in 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 solutions for data storage (data lakes, data warehouses, object storage (S3))
• System architecture: Ability to design an end-to-end ML system, taking into account scalability, robustness, maintenance, and hardware constraints.

Hard Skills

• Databases: MySQL, PostgreSQL, Neo4j, Milvus
• AI Framework: PyTorch, tensorflow, huggingface, mlflow, sklearn, OpenCV
• Programming Languages: Python (R is a plus)
• Database Paradigms: NoSQL, SQL
• Orchestration: Kubernetes, Kubeflow
• Cloud Platforms: Azure, AWS
• Versioning (code and models): MlFlow, dvc, Neptune, Git, Github, Gitlab

Languages

Language knowledge: You have at least a good command of English as well as one of the two national languages (NL/FR).

Soft Skills

• Ability to unite: Know how to align heterogeneous profiles around a common objective.
• Sense of priorities: Identify critical tasks to achieve objectives, keep a long-term vision to anticipate the next steps, and reorganize work according to unforeseen events or new elements that arise during the project.
• Clear and spontaneous communication: Communicate fluently, convey the right message, at the right time and at the right level. Be able to explain technical concepts to non-technicians.
• Problem solving and analytical thinking: Approach problems in a structured way, identify root causes, and propose pragmatic and effective solutions. Be able to take a step back to evaluate several scenarios and choose the solution best suited to the context.
• Collaboration: Work constructively with all stakeholders, encourage exchanges and co-construction of solutions. Be attentive to everyone's needs and constraints to foster a positive and productive working environment.
• Attention to detail: Pay attention to the technical, functional, and organizational aspects of projects. Ensure code quality, model robustness, deliverable compliance, and adherence to organizational standards.
• Rigor: Systematically apply good practices and methodologies, document work precisely, and ensure constant monitoring of project progress in compliance with deadlines and quality requirements.