Role overview
Are you passionate about turning complex data into intelligent, production-ready solutions while supporting the future of open-access science? Join our Data Intelligence team in our Kraków office as a Senior Data Scientist and help build advanced machine learning models that power discovery and insight. In this role, you will work across the full lifecycle of data products – from exploration and modelling to deployment and monitoring – contributing to initiatives such as ontology development, automated paper tagging, trend analysis, and performance monitoring, all aimed at making scientific knowledge more accessible and impactful.
*This is a fully in-office role based in Kraków.
Core Responsibilities**
- Advanced Data Analysis and Modeling: Design, develop, and validate statistical models and machine learning solutions to support editorial performance analysis, trend detection, and strategic decision-making.
- Machine Learning Development and Deployment: Build, deploy, and maintain machine learning models and pipelines, ensuring robustness, scalability, and reliable performance in production environments.
- Data Processing and Feature Engineering: Lead data preprocessing, feature engineering, and dataset validation activities using data from internal editorial systems and external sources.
- Ontology and Automated Classification: Contribute to the development and refinement of ontology structures and automated paper-tagging systems, including model evaluation and continuous improvement.
- Trend Analysis and Forecasting: Develop analytical tools and predictive models to identify emerging research topics and publication dynamics across journals.
- MLOps and Platform Integration: Collaborate with Data Engineering to integrate models into the data intelligence platform, supporting APIs, monitoring, and model lifecycle management.
What you'll work on
- Documentation and Reproducibility: Ensure clear documentation of data pipelines, models, and analytical workflows to promote reproducibility and maintainability.
- Quality and Performance Monitoring: Contribute to monitoring data quality, model performance, and system reliability, including alerting and anomaly detection.
- Cross-Functional Collaboration: Work closely with editorial, analytics, and technical teams to translate business needs into effective solutions.
What we're looking for
- Certification in Python or SQL.
- Coursework or certifications in Machine Learning or Data Analytics (e.g., Coursera, edX, IBM, Google or similar programmes).
Tags & focus areas
Used for matching and alerts on DevFound Machine Learning Data Science Ai