Senior Data Scientist

Nasze wymagania: Bachelor’s degree in Data Science, Statistics, Mathematics, Computer Science, or another STEM-related field. Strong background in data science, statistics, and analytical problem-solving. Advanced programming skills in Python and SQL. Proven experience developing, evaluating, and deploying machine learning models. Advanced proficiency in data visualisation tools and techniques to communicate insights effectively. Experience with version control systems (Git) and collaborative development workflows. Strong working knowledge of Microsoft O365 tools. Excellent written and spoken English. Analytical thinking and problem-solving. Effective collaboration within multidisciplinary teams. Mile widziane: Certification in Python or SQL. Coursework or certifications in Machine Learning or Data Analytics (e.g., Coursera, edX, IBM, Google or similar programmes). O projekcie: 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. Zakres obowiązków: 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. 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. Oferujemy: A dynamic and innovative team at the forefront of data technology. Opportunity to take part in impactful projects. Work in a collaborative environment that values creativity and diversity. Private medical care (fully covered). MultiSport card (partially covered). Team building activities.