Remote AI/ML Data Scientist - MLOps & Modeling

Quik Hire Staffing

Piemonte

Remoto

EUR 78.000 - 113.000

Tempo pieno

7 giorni fa
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Descrizione del lavoro

Quik Hire Staffing is recruiting a Data Scientist specialized in AI/ML for a fully remote, full-time role. You will design, train, and deploy models, work with cross-functional teams, and help automate ML workflows.

The ideal candidate has strong Python skills, experience with scikit-learn/TensorFlow/PyTorch, SQL, and cloud deployments (AWS/GCP/Azure), and can work independently in a remote setting.

Competenze

  • Proficiency in Python and libraries such as scikit-learn, TensorFlow, or PyTorch.
  • Experience with SQL for data extraction, transformation, and analysis.
  • Strong background in statistical modeling and experimental design.
  • Familiarity with cloud platforms including AWS, GCP, or Azure for model deployment.
  • Ability to work independently in a remote environment with minimal supervision.

Mansioni

  • Design, train, and optimize machine learning models for classification, regression, and clustering tasks.
  • Preprocess and analyze large-scale structured and unstructured datasets to extract actionable insights.
  • Implement and maintain MLOps pipelines for model deployment, monitoring, and retraining.
  • Develop and document reproducible experiments using Python, Jupyter notebooks, and version control systems.
  • Present findings and recommendations to stakeholders through clear visualizations and technical reports.

Conoscenze

Python
SQL
Statistical modeling
Experimental design
Remote work

Strumenti

scikit-learn
TensorFlow
PyTorch
AWS
GCP/Azure

Descrizione del lavoro

Quik Hire Staffing is recruiting a Data Scientist specialized in AI/ML for a fully remote, full-time role. You will design, train, and deploy models, work with cross-functional teams, and help automate ML workflows.

The ideal candidate has strong Python skills, experience with scikit-learn/TensorFlow/PyTorch, SQL, and cloud deployments (AWS/GCP/Azure), and can work independently in a remote setting.

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