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

• 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.

Responsibilities

• 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.