Data Scientist

Keystone Solutions
Brussel, Belgium
18 days ago
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Role details

Contract type
Temporary contract
Employment type
Full-time (> 32 hours)
Experience level
Experienced
Experience required
3 years minimum
Working hours
Regular working hours
Languages
Dutch, English, French
Job source

Tech stack

Artificial Intelligence Amazon Web Services Amazon S3 Microsoft Azure Big Data Cloud Engineering Computer Programming Databases Continuous Delivery Continuous Integration Data Warehousing Github
+28 more
Python (Programming Language) PostgreSQL Machine Learning MySQL Neo4j NoSQL OpenCV Tensorflow Software Engineering SQL Databases Systems Architecture Unstructured Data Management of Software Versions Google Cloud Data Storage Technologies Pytorch Deep Learning Gitlab Git Containerization Data Lakes Scikit Learn Kubernetes Information Technology HuggingFace Non-relational Database Machine Learning Operations Docker

Job description

As a Data Scientist, you will be engaged in a consultancy mission at a client site representing Keystone Solutions. 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. Your responsibilities will include the development of machine learning pipelines, as well as their monitoring and maintenance. You will also be responsible for deploying AI models for the organization, primarily on-premise, ensuring the implementation of best practices in programming and machine learning within your projects. Staying updated with the latest advancements in MLOps and machine learning will be essential. Attention to security, ethics, and legal aspects is a valued plus., * Develop and maintain machine learning pipelines.

  • Deploy AI models primarily on-premise.
  • Implement best programming and machine learning standards.
  • Conduct technological monitoring in MLOps and machine learning., At Keystone Solutions, you will experience a dynamic consultancy environment where you will work on diverse projects across various client settings. Our commitment to turbo-charged learning ensures that you will have ample opportunities for professional development and career growth. Being a

Requirements

You hold a master’s or doctorate in computer science, AI, or a relevant field and have a minimum of 3 years of experience in data science, MLOps, and ML. You possess expertise in the following areas:

  • On-premise and cloud development: Expertise in developing and deploying AI solutions on-premise and in the cloud (Azure, AWS, GCP).
  • 3+ years of industry experience: Experience in ML, MLOps, and big data with a focus on large-scale deployment.
  • Theoretical background and practical expertise in ML and deep learning.
  • Database Paradigm (SQL & NoSQL): Advanced knowledge in relational and non-relational databases (SQL and NoSQL) including PostGres, MySQL, Milvus, Neo4J, etc.
  • ML MLOps: Demonstrable experience in deploying ML models and expertise in MLOps.
  • Focus on big data: Experience in handling large structured and unstructured datasets.
  • Containerization and deployment: Experience with Docker and Kubernetes, as well as orchestration tools like Kubeflow. Mastery of ML pipelines (Kubeflow, MLflow, SageMaker, etc.).
  • CI/CD for ML: Mastery of implementing CI/CD for ML models and associated code.
  • Data Storage: Experience with various data storage solutions (data lakes, data warehouses, object storage (S3)).
  • System architecture: Ability to design an end-to-end ML system considering scalability, robustness, maintenance, and hardware constraints.

Hard Skills:

  • Databases: MySQL, PostgreSQL, Neo4j, Milvus
  • AI Framework: huggingface, mlflow, PyTorch, tensorflow, sklearn, OpenCV, vllm
  • Programming Languages: Python (R is a plus)
  • Orchestration and containerization: Docker, Kubernetes, Kubeflow
  • Software engineering: uv, ruff, black
  • Cloud Platforms: Azure, AWS
  • Versioning (code and models): MlFlow, Git, Github, Gitlab

Languages:

You are proficient in English and one of the two national languages (NL/FR).

Soft Skills:

  • Ability to unite diverse profiles around a common goal.
  • Prioritization skills: Identify critical tasks to achieve objectives while maintaining a long-term vision.
  • Clear and spontaneous communication: Effectively convey the right message at the right time and level.
  • Problem-solving and analytical thinking: Approach problems systematically and propose pragmatic solutions.
  • Collaboration: Work constructively with all stakeholders, fostering exchanges and co-construction of solutions.
  • Attention to detail: Ensure quality in code, model robustness, and compliance with organizational standards.
  • Rigor: Apply best practices and methodologies consistently, documenting work accurately., * Azure - Level: Confirmed - Most recent: Any time
  • Docker - Level: Confirmed - Most recent: Any time
  • GIT - Level: Confirmed - Most recent: Any time
  • GitHub - Level: Confirmed - Most recent: Any time
  • Gitlab - Level: Confirmed - Most recent: Any time
  • huggingface - Level: Confirmed - Most recent: Any time
  • kubeflow - Level: Confirmed - Most recent: Any time
  • Kubernetes - Level: Confirmed - Most recent: Any time
  • milvus - Level: Confirmed - Most recent: Any time
  • mlflow - Level: Confirmed - Most recent: Any time
  • MySql - Level: Confirmed - Most recent: Any time
  • Neo4J - Level: Confirmed - Most recent: Any time
  • PostgreSQL - Level: Confirmed - Most recent: Any time
  • Python - Level: Confirmed - Most recent: Any time
  • Pytorch - Level: Confirmed - Most recent: Any time
  • ruff - Level: Confirmed - Most recent: Any time
  • Tensorflow - Level: Confirmed - Most recent: Any time

Language requirements:

Dutch or French Level Active knowledge English Level Active knowledge

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