Remote Data Scientist — AI/ML & MLOps Innovator

Quik Hire Staffing

Verona

Remoto

EUR 78.000 - 113.000

Tempo pieno

6 giorni fa
Candidati tra i primi
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Descrizione del lavoro

Quik Hire Staffing is hiring for a Data Scientist (ML) to work on a full-time, remote basis. You will design, train, and deploy machine learning models to improve predictive accuracy for client datasets and collaborate with cross-functional teams to drive data-driven solutions.

You will develop reproducible experiments using Python, Jupyter notebooks, and version control, and implement scalable MLOps pipelines for deployment, monitoring, and retraining, while presenting findings with clear

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 ML models for classification, regression, and clustering.
  • 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
Statistics
Experimental design
Remote work

Strumenti

scikit-learn
TensorFlow
PyTorch
AWS
GCP
Azure
Jupyter
Git

Descrizione del lavoro

Quik Hire Staffing is hiring for a Data Scientist (ML) to work on a full-time, remote basis. You will design, train, and deploy machine learning models to improve predictive accuracy for client datasets and collaborate with cross-functional teams to drive data-driven solutions.

You will develop reproducible experiments using Python, Jupyter notebooks, and version control, and implement scalable MLOps pipelines for deployment, monitoring, and retraining, while presenting findings with clear

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