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Data Science engineer (Remote)

Quik Hire Staffing
Remote, UAE
Contract
Entry
Remote
Discovered 1 weeks ago
PythonNumPyPandasScikit-learnTensorFlowPyTorch
Free

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Role Overview

The employer is seeking a Data Science Engineer for a client contract role.

The role focuses on designing, building, and deploying machine learning models and data pipelines for scalable AI solutions.

The engineer will collaborate with cross-functional teams to translate business requirements into technical solutions.

Location

  • The role is remote and can be performed from anywhere.

Job Type and Payout

  • The job type is contract.
  • Payout is competitive and based on experience.

Key Responsibilities

  • Develop and maintain production-grade data science models using Python and relevant frameworks.
  • Design and implement data pipelines to process large-scale datasets for model training and inference.
  • Collaborate with software engineers to integrate models into production systems and APIs.
  • Optimize models for performance, scalability, and cost-efficiency in cloud environments.
  • Conduct testing and validation to ensure model accuracy, reliability, and compliance.

Required Skills and Qualifications

  • Proficiency in Python with experience in NumPy, Pandas, and Scikit-learn.
  • Experience with TensorFlow, PyTorch, or similar machine learning frameworks.
  • Strong background in statistical modeling, regression, classification, and clustering.
  • Familiarity with AWS, GCP, or Azure and big data tools such as Spark or Hadoop.
  • Experience with SQL and database systems for data extraction and transformation.
  • Ability to write clean, maintainable, and well-documented code.
  • Understanding of MLOps practices, including model deployment and monitoring.
  • Experience with version control systems such as Git.

Opportunity Context

The role supports the development of AI solutions for a global technology, information, and internet industry leader.

The position involves solving complex data challenges in a collaborative, remote-first environment.

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