Data Scientist

Yechte Consulting Ltd; Brussel Hoofdstad; On-site; EUR 70,000 - 120,000; Full time

Benefits offered by this job

Remote-friendly?

Job summary

Yechte Consulting Ltd seeks an experienced ML/DS engineer to deploy models on AWS and manage end-to-end ML pipelines. You will monitor performance, implement IaC, and ensure secure, scalable infrastructure across cloud and on-premise environments.

You will collaborate with data scientists and engineers, stay current with ML and DevOps practices, and contribute to FinOps improvements while delivering reliable, data-driven solutions.

Qualifications

• Bachelor’s or Master’s degree in Computer Science, IT, Data Science or related field.
• Proven experience as Data Scientist, ML Engineer, Data Engineer, or similar role.
• Experience conducting both business and technical analysis.
• Strong system architecture understanding and scalable design ability.
• Experience with Python and data science ecosystem.
• Strong MLOps knowledge: deployment, monitoring, lifecycle management.
• Hands-on experience with cloud-based and on-prem infrastructure.
• Proficiency in Python and data ecosystems.
• Experience with CI/CD pipelines, Docker, Kubernetes.
• Strong SQL knowledge; NoSQL familiarity.
• Excellent analytical and problem-solving skills.
• Strong communication and stakeholder management; collaboration capable.
• Independent work style with multi-task prioritization in fast-paced environments.
• Proficiency in Dutch and English

Responsibilities

• Deploy machine learning models using AWS solutions.
• Monitor performance and scalability of deployed models in cloud and on-premise environments.
• Implement best practices for version control, model tracking, and lifecycle management.
• Design scalable, reliable, and secure cloud and on‑premise infrastructure for ML projects.
• Ensure seamless integration between infrastructure components.
• Implement and maintain CI/CD pipelines for ML projects.
• Adopt Infrastructure as Code (IaC) principles for consistency and repeatability.
• Collaborate with data scientists, data engineers, and stakeholders to meet project requirements.
• Stay up-to-date with ML, cloud, DevOps and MLOps practices.
• Identify and implement improvements including FinOps.
• Participate in incident response related to data integrity and service availability.
• Troubleshoot and resolve performance or data quality issues promptly.

Skills

Python

MLOps

CI/CD

Docker

Kubernetes

SQL

NoSQL

Data analysis

DevOps practices

Communication

Dutch-English

Education

Bachelor’s or Master’s degree in Computer Science/IT/Data Science/related field

Tools

AWS

Docker

Kubernetes

dbt

Dagster

SageMaker

Job description

Job Responsibilities

• Deploy machine learning models, specifically using AWS solutions.
• Monitor and maintain the performance and scalability of deployed models, in both cloud and on-premise environments.
• Implement best practices for version control, model tracking, and model lifecycle management.
• Design and manage scalable, reliable, and secure cloud and on-premise infrastructure for machine learning projects.
• Ensure seamless integration between different infrastructure components.
• Implement and maintain CI/CD pipelines for machine learning projects.
• Adopt sound Infrastructure as Code (IaC) principles to ensure consistency and repeatability, enhancing data-driven workflows.
• Work closely with data scientists, data engineers, and other stakeholders to understand project requirements and deliver optimal solutions.
• Stay up-to-date with the latest developments in machine learning, cloud technologies, and DevOps and MLOps practices.
• Identify and implement improvements to existing workflows and systems, including FinOps.
• Participate in incident response activities, especially those related to data integrity and service availability, to help teams dig into root cause analysis.
• Help troubleshoot and resolve performance or data quality-related issues promptly.

Must Have Skills

• Bachelor’s or Master’s degree in Computer Science, Information Technology, Data Science, or a related field.
• Proven experience as a Data Scientist, Machine Learning Engineer, Data Engineer, or in a similar role.
• Experience conducting both business and technical analysis.
• Strong understanding of system architecture, with the ability to translate business requirements into scalable technical designs and solutions.
• Experience performing data analysis using Python through scripting and Jupyter Notebooks.
• Strong understanding of MLOps principles, including model deployment, monitoring, and lifecycle management.
• Hands-on experience with both cloud-based and on-premises infrastructure.
• Proficiency in Python and its data science ecosystem.
• Experience with DevOps practices and tools, including:
• CI/CD pipelines.
• Containerization using Docker.
• Orchestration platforms such as Kubernetes or Amazon ECS.
• Strong knowledge of SQL and familiarity with NoSQL databases.
• Excellent analytical and problem-solving skills, with the ability to think critically and creatively.
• Strong communication and stakeholder-management skills, with the ability to collaborate effectively across technical and business teams.
• Ability to work independently, prioritize effectively, and manage multiple tasks in a fast-paced environment.
• Professional working proficiency in Dutch and English.

Nice to have

• Experience with Amazon SageMaker and other AWS services.
• Knowledge of modern data-engineering practices and frameworks, such as dbt and/or Dagster.
• Familiarity with additional programming languages, such as R, Java, or C++.
• Experience with Infrastructure as Code tools and practices.
• Knowledge of model tracking, model registries, automated retraining, and model-monitoring solutions.
• Experience with FinOps, cloud-cost optimization, and performance optimization for machine learning workloads.
• AWS MLOps practices commonly include model training, deployment, monitoring, versioning, and lifecycle management at scale.

What's great in the job? Great team of smart people, in a friendly and open culture Expand your knowledge of various business industriesCreate content that will help our users on a daily basis Real responsibilities and challenges in a fast evolving company