Data Scientist

h3Job Responsibilities /h3ulliDeploy machine learning models, specifically using AWS solutions. /liliMonitor and maintain the performance and scalability of deployed models, in both cloud and on-premise environments. /liliImplement best practices for version control, model tracking, and model lifecycle management. /liliDesign and manage scalable, reliable, and secure cloud and on-premise infrastructure for machine learning projects. /liliEnsure seamless integration between different infrastructure components. /liliImplement and maintain CI/CD pipelines for machine learning projects. /liliAdopt sound Infrastructure as Code (IaC) principles to ensure consistency and repeatability, enhancing data-driven workflows. /liliWork closely with data scientists, data engineers, and other stakeholders to understand project requirements and deliver optimal solutions. /liliStay up-to-date with the latest developments in machine learning, cloud technologies, and DevOps and MLOps practices. /liliIdentify and implement improvements to existing workflows and systems, including FinOps. /liliParticipate in incident response activities, especially those related to data integrity and service availability, to help teams dig into root cause analysis. /liliHelp troubleshoot and resolve performance or data quality-related issues promptly. /li /ulh3Must Have Skills /h3ulliBachelor’s or Master’s degree in Computer Science, Information Technology, Data Science, or a related field. /liliProven experience as a Data Scientist, Machine Learning Engineer, Data Engineer, or in a similar role. /liliExperience conducting both business and technical analysis. /liliStrong understanding of system architecture, with the ability to translate business requirements into scalable technical designs and solutions. /liliExperience performing data analysis using Python through scripting and Jupyter Notebooks. /liliStrong understanding of MLOps principles, including model deployment, monitoring, and lifecycle management. /liliHands-on experience with both cloud-based and on-premises infrastructure. /liliProficiency in Python and its data science ecosystem. /liliExperience with DevOps practices and tools, including: /liliCI/CD pipelines. /liliContainerization using Docker. /liliOrchestration platforms such as Kubernetes or Amazon ECS. /liliStrong knowledge of SQL and familiarity with NoSQL databases. /liliExcellent analytical and problem-solving skills, with the ability to think critically and creatively. /liliStrong communication and stakeholder-management skills, with the ability to collaborate effectively across technical and business teams. /liliAbility to work independently, prioritize effectively, and manage multiple tasks in a fast-paced environment. /liliProfessional working proficiency in Dutch and English. /li /ulh3Nice to have /h3ulliExperience with Amazon SageMaker and other AWS services. /liliKnowledge of modern data-engineering practices and frameworks, such as dbt and/or Dagster. /liliFamiliarity with additional programming languages, such as R, Java, or C++. /liliExperience with Infrastructure as Code tools and practices. /liliKnowledge of model tracking, model registries, automated retraining, and model-monitoring solutions. /liliExperience with FinOps, cloud-cost optimization, and performance optimization for machine learning workloads. /liliAWS MLOps practices commonly include model training, deployment, monitoring, versioning, and lifecycle management at scale. /li /ulpWhat'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 /p