Senior Data Science Operations Specialist

12 hours ago

Athens, Attica, Greece beBeeDataScience Full time

Job Description:

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We are seeking a skilled Senior Data Science Operations Specialist to join our team and play a key role in bridging the gap between our Data Science and Infrastructure teams. As a vital member of our data operations group, you will be responsible for supporting the Data Science team in MLOps-related tasks while also helping in DevOps initiatives, including CI/CD pipeline creation, provisioning of cloud resources using tools like Terraform, and Kubernetes orchestration.

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Main Responsibilities:

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  • Design, implement, and maintain scalable MLOps pipelines on AWS using services such as SageMaker, EC2, EKS, S3, Lambda, and other relevant AWS tools
  • Collaborate with the platform team to troubleshoot Kubernetes clusters (EKS) to orchestrate the deployment of machine learning models and other microservices
  • Develop and maintain CI/CD pipelines for model and application deployment, testing, and monitoring
  • Streamline the model development lifecycle, from experimentation to production deployment, by collaborating closely with Data Science and DevOps teams
  • Implement security best practices, including network security, data encryption, and role-based access controls within the AWS infrastructure
  • Monitor, troubleshoot, and optimize data and ML pipelines to ensure high availability and performance
  • Set up and manage model monitoring systems for performance drift, ensuring continuous model improvement
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Requirements:

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  • Bachelor's degree in Computer Science, Engineering, or related field
  • 1+ years of hands-on experience in MLOps, DevOps, or related fields
  • Knowledge and preferable working experience in AWS services for machine learning, such as SageMaker, EKS, S3, EC2, Lambda, and others
  • Exposure to Kubernetes for container orchestration
  • Experience with Docker
  • Exposure to infrastructure-as-code tools such as Terraform or CloudFormation
  • Familiarity with CI/CD tools such as GitLab CI
  • Understanding machine learning model lifecycle
  • Familiarity with monitoring and logging solutions like Prometheus, Grafana, CloudWatch, and ELK Stack
  • Understanding of networking concepts and cloud security best practices
  • Proficiency in Python and Bash, and comfortable working in Linux environments
  • Strong problem-solving and communication skills
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Desirable Skills:

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  • Experience working with serverless architectures and event-driven processing on AWS
  • Familiarity with advanced Kubernetes concepts such as Helm
  • Experience with Data Engineering pipelines, ETL processes, or big data platforms
  • Experience with ML frameworks like TensorFlow, PyTorch, and Keras
  • Experience with ML platforms like Kubeflow and/or SageMaker
  • Experience with workflow engines like Argo Workflows and/or Airflow
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Benefits:

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  • Attractive remuneration package plus performance-related reward
  • Private health insurance
  • Corporate pension fund
  • Intellectually stimulating work environment
  • Continuous personal development and international training opportunities
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Hiring Experience:

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  • Let's Connect – Intro Chat with Talent Acquisition
  • Deep Dive – First Interview with Your Future Team
  • Final Connection – Final Interview

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