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Data Science Operations Specialist

1 tydzień temu

Wrocław, Polska DCG Pełny etat
Job Description

As a recruitment company, DCG prides itself on understanding that every business relies on experienced professionals to drive success. Our unique management style and partnership approach enable us to meet our clients' needs and provide continuous support.

We are currently seeking a skilled Data Science Operations Specialist to join our team due to our ongoing growth and the large number of data science projects we undertake for our partners.

Key Responsibilities

  • Data Science Solution Optimization: Design and implement scalable data science solutions in cloud-based environments (Azure) to drive business value.
  • DevOps and CI/CD: Participate in the end-to-end lifecycle of data science projects through the use of DevOps practices, code, experiment, and model management.
  • Coding Best Practices: Write well-designed, testable, efficient code to ensure high-quality deliverables.
  • Collaboration with Engineering: Work closely with engineering teams to continuously improve the way we consume data and deploy models in production.
  • Pipeline Monitoring and Troubleshooting: Design and lead on monitoring, troubleshooting, debugging, and incident management for our ML pipelines.
  • ML Ops Expertise: Be a trusted advisor and evangelist to the team and stakeholders on various aspects of ML Ops, including scaling and throughput, infrastructure, and deployment strategies.

Requirements

  • Professional Experience: 2+ years of professional experience in ML Ops or ML engineering, particularly in productionizing and scaling ML models.
  • Language Skills: Business-ready command of English, written and spoken.
  • Azure Cloud Environment: Broad familiarity with Azure cloud environment and Databricks, including its setup and maintenance as an ML platform.
  • Software Development Best Practices: Proven experience with software development best practices, including testing, continuous integration, and DevOps tools.
  • Data Science Lifecycle: Good understanding of the data science lifecycle and the way data scientists work to deliver value.
  • Programming Skills: Advanced proficiency with Python and SQL in version control systems (git), plus their use in building ML & data pipelines.
  • Agile Software Development: Familiarity with agile software development lifecycle (SCRUM, Kanban, etc.).
  • Code Quality: Attention to clarity of code, ease of development, and correctness of implementations.

Offer

  • Private Medical Care
  • Sports Card Co-Financing
  • Dedicated Consultant Support
  • Employee Referral Program