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Data Scientist

Master-Works
Riyadh, KSA
Full-time
Entry · 2+ years experience
Onsite
Discovered 2 weeks ago
PythonRSQL

Full Job Posting

Key Responsibilities

  • Design, develop, test, and deploy machine learning models and predictive analytics solutions.
  • Extract, process, and analyze large and complex datasets from multiple sources.
  • Perform exploratory data analysis (EDA) to identify trends, patterns, and actionable insights.
  • Develop and maintain robust statistical and machine learning pipelines for production environments.
  • Collaborate with stakeholders and business teams to understand requirements and translate them into data science solutions.
  • Apply statistical modeling and machine learning techniques to address business problems.
  • Evaluate and optimize model performance, accuracy, and scalability.
  • Research and evaluate emerging data science tools, techniques, and methodologies.
  • Present data-driven findings and recommendations to both technical and non-technical stakeholders.

Required Qualifications & Skills

  • Bachelor’s degree or higher in Data Science, Computer Science, Statistics, Mathematics, Engineering, or a related field.
  • 2+ years of professional experience in Data Science, Machine Learning, or a related field.
  • Strong proficiency in Python ; knowledge of R is a plus.
  • Advanced SQL skills and experience working with large datasets.
  • Strong understanding of machine learning, statistical modeling, and predictive analytics.
  • Experience with data preprocessing, feature engineering, model evaluation, and optimization.
  • Experience deploying machine learning models or analytical solutions into production environments.
  • Strong analytical, problem-solving, and communication skills.
  • Ability to work effectively with cross-functional teams and translate business requirements into technical solutions.

Preferred Qualifications

  • Experience with cloud platforms, big data technologies, or ML/AI frameworks.
  • Familiarity with MLOps and production machine learning practices.
  • Experience working in an enterprise or business-focused environment.

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