Senior Data Scientist / Machine Learning Engineer

Ukraine. Turkey. Greece. Romania. EgyptFull-TimeSenior
Salary not disclosed
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Job Details

Experience
5+ years
Required Skills
AWSPostgreSQLPythonSQLGCPMicrosoft SQL ServerMySQLPyTorchAzureTensorflowscikit-learnMLOps

Requirements

  • Bachelor’s or Master’s degree in Data Science, Machine Learning, Computer Science, Statistics, or a related field
  • 5+ years of experience in data science, machine learning, or applied AI roles
  • Strong proficiency in Python for data processing and machine learning
  • Hands-on experience with machine learning frameworks and libraries (scikit-learn, TensorFlow, PyTorch, XGBoost)
  • Strong understanding of supervised and unsupervised learning, deep learning, and model evaluation techniques
  • Expertise in SQL and experience with relational databases (PostgreSQL, MySQL, MS SQL)
  • Experience deploying machine learning models into production environments
  • Familiarity with MLOps practices (model versioning, CI/CD, monitoring, retraining)
  • Experience with cloud platforms such as AWS, GCP, or Azure
  • Understanding of data governance, model ethics, and data privacy considerations
  • Strong communication skills with the ability to work effectively with U.S.-based stakeholders

Responsibilities

  • Design, develop, and deploy machine learning models for real-world production use cases
  • Analyze large and complex datasets to extract insights that inform model development and optimization
  • Build end-to-end ML pipelines, including data preprocessing, feature engineering, model training, evaluation, and deployment
  • Collaborate with data engineers, software engineers, product managers, and business stakeholders to define machine learning requirements
  • Implement model monitoring, performance tracking, and retraining strategies
  • Optimize models for scalability, performance, and reliability in cloud-based environments
  • Ensure data quality, reproducibility, and adherence to best practices in ML development
  • Translate machine learning outcomes into clear, actionable insights for technical and non-technical audiences
  • Contribute to improving ML standards, tools, and best practices across teams
  • Mentor junior data scientists and machine learning engineers
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