Senior Data Scientist @

4 days ago

Remote, Czech Republic Devire Full time
  • At least 4 years of hands-on experience in ML, data science, or a similar role, with demonstrated ownership of deployed ML systems.
  • Strong grasp of core ML techniques: regression, classification, clustering, regularization, ensemble methods, neural networks, etc.
  • Solid experience with Natural Language Processing (NLP) from traditional methods (TF-IDF, topic modeling) to transformer-based architectures (e.g., BERT, GPT, T5).
  • Working knowledge of recommendation engines, such as collaborative filtering, content-based filtering, or hybrid models.
  • Expertise in Python and ML/data libraries such as scikit-learn, xgboost, lightgbm, pandas, numpy, PyTorch or TensorFlow/Keras.
  • Experience with at least one major cloud platform (AWS, Azure, GCP), including usage of managed ML services or containerized deployment workflows.
  • Understanding of MLOps principles, including reproducibility, model monitoring, A/B testing, and automation.

Devire IT Outsourcing is a form of cooperation dedicated to IT professionals, based on the principles of own business - B2B, implementing projects for clients running innovative and modern projects.

With Our client who is a leading company in the European market offering HR-tech solutions for innovative recruitment, which was recently recognized as a key leader in its industry, we are looking for Senior Data Scientist.

  • Salary: 140-170 PLN net+VAT/h, B2B via Devire
  • Remote work model 
  • Benefits: Multisport card, private medical care, life insurance 
  • Long-term cooperation 
  • Flexible working hours, Polish time zone
,[Design, build, and scale machine learning systems, including recommendation engines and predictive models for real-world business applications., Analyze both structured and unstructured data, applying advanced ML and NLP techniques to extract insights and power intelligent products., Own the end-to-end model lifecycle: from data preprocessing, experimentation, model training, evaluation, and tuning to deployment and continuous monitoring in production environments., Apply MLOps best practices, ensuring reproducibility, versioning, CI/CD integration, and performance monitoring., Translate complex business problems into robust ML solutions in collaboration with product, engineering, and domain experts., Communicate clearly and effectively with both technical and non-technical stakeholders, articulating model behavior, assumptions, and trade-offs., Continuously evaluate and implement state-of-the-art techniques, staying current with developments in ML, NLP, and deep learning., Contribute to team growth, sharing expertise and mentoring peers in modeling, tooling, and system design.] Requirements: Natural language processing, Python, scikit-learn, pandas, NumPy, PyTorch, TensorFlow, Keras, Cloud platform, Azure, GCP, MLOps, Testing

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