Data Scientist

Job Description

The following information provides an overview of the skills, qualities, and qualifications needed for this role.

Central Employment are working in partnership with a long term eCommerce Web-Print Specialist, as they look to recruit a Data Scientist , joining the growing Engineering team in Newcastle.

Data Scientist profile:

My client is seeking a Data Scientist with a strong technical background in machine learning and data analysis. In this role, you will be responsible for building and fine-tuning machine learning models that drive key business outcomes. These models will be integrated into various systems, including our website, reporting tools, and analytics platforms. You will work closely with the Data Engineering team to ensure the deployment, integration, and scaling of these models within our data infrastructure.

Key Responsibilities:

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• Design, develop, and optimize machine learning models to solve business challenges such as customer segmentation, predictive analytics, and recommendations.
  
• Utilize Python and SQL for data preprocessing, feature engineering, model training, and validation.
  
• Experiment with a variety of algorithms and techniques to enhance model accuracy and performance.
  
• Conduct in-depth data analysis to extract insights and identify trends that inform model development.
  
• Engineer and select features that improve model performance, ensuring relevance and robustness.
  
• Collaborate with the data engineering team to guarantee that clean, well-structured data is available for model training and evaluation.
  
• Engage in rigorous testing and validation processes to ensure models are ready for scaling and integration across various business applications
  
• Work in close collaboration with the Senior Data Engineer to prepare models for production, ensuring they meet all criteria for deployment within the data platform.
  

Experience:

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• 3+ years of experience as a Data Scientist, with a proven ability to develop and deploy machine learning models in a production environment.
  
• Expertise in Python (e.g., scikit-learn, TensorFlow, PyTorch) and SQL.
  
• Familiarity with AWS cloud services, particularly those relevant to data science and machine learning.
  
• Strong background in working with large datasets and applying advanced statistical methods.