Summary: Seeking a Lead Data Scientist to shape global research intelligence by designing and deploying cutting-edge analytics and machine learning models for scholarly datasets. Highlights: 1. Shape the future of global research intelligence 2. Combine deep technical work with real-world impact 3. Provide technical leadership and mentorship We are seeking a ***Lead Data Scientist***, to help shape the future of global research intelligence at the Institute for Scientific Information (ISI), part of the Research \& Analytics business unit in Clarivate. In this role, you will design and deploy cutting\-edge analytics, machine learning, and network models using some of the world’s largest and richest scholarly datasets influencing how research impact, collaboration, and societal value are understood worldwide. You will tackle intellectually ambitious problems, from building responsible next\-generation research metrics to uncovering insights hidden in citation graphs, full text, patents, and other data. Working at the intersection of data science and product innovation, you will translate advanced analytics into trusted solutions used by universities, governments, and research leaders. You will provide technical leadership and mentorship to junior colleagues while championing rigorous methodology, transparency, and responsible AI. If you are seeking an opportunity to combine deep technical work with real\-world impact on the integrity, evaluation, and future direction of science, we would love to speak with you. **About You – experience, education, skills, and accomplishments** * Bachelor’s degree or equivalent in Computer Science, Statistics, Engineering, or related field * At least 7 years of relevant experience with Python or similar data analysis and data science ecosystem, SQL, data visualization platforms (Tableau, Power BI or similar) * Previous experience with existing large language models (LLMs), including where LLMs are useful in research analytics workflows, where LLMs are not appropriate or reliable, the inherent limitations of LLMs and machine learning systems. * Practical experience in topic modelling, network analysis (e.g., community detection and clustering), text mining **It would be great if you also had . . .** * Knowledge of academic research and understanding of the research ecosystem * Prior experience in analysis of data and content in Web of Science, Journal Citation Reports and InCites **What will you be doing in this role?** * Conduct advanced data engineering and analytics on large\-scale research datasets, including structured data (citation metadata, affiliations, funding records, journal metrics, classifications) and unstructured data (titles, abstracts, full text, patents), to generate actionable insights for research evaluation, benchmarking, and research intelligence. * Lead the design, development, and deployment of advanced machine learning and network analytics models to support use cases such as citation analysis, research impact assessment, topic modelling, collaboration network analysis, trend detection, and predictive analytics aligned with research policy and institutional decision\-making needs. * Partner closely with product, engineering, data platform, domain experts, and client\-facing teams to translate research analytics requirements into deployable models and integrate insights into customer\-facing platforms, APIs, dashboards, and analytical workflows. Perform statistical analyses to influence decision\-making and optimize processes across various departments. * Apply rigorous statistical methods and experimental design to validate models, assess data quality and bias, quantify uncertainty, and ensure methodological soundness in metrics used for research assessment, rankings, and benchmarking. * Provide technical leadership and mentorship to junior ISI colleagues, promoting best practices in model development, code quality, documentation, peer review, and responsible use of data and AI in a research evaluation context. * Continuously evaluate emerging data science methodologies and technologies, including advances in NLP, graph analytics, and machine learning, assessing their suitability, scalability, interpretability, and impact on product quality and customer trust. * Contribute to internal and external communications (e.g. reports, research papers, white papers, speaking engagements) to explain novel findings and provide suitable interpretative support to the global research analytics community **About the Team** The Institute for Scientific Information at Clarivate has pioneered the organization of the world's research information for more than half a century. Today it remains committed to promoting integrity in research while improving the retrieval, interpretation and utility of scientific information. It maintains the knowledge corpus upon which the Web of Science index and related information and analytical content and services are built. It disseminates that knowledge externally through events, conferences and publications while conducting primary research to sustain, extend and improve the knowledge base. For more information, please visit https://clarivate.com/isi. **Hours of Work** This is a full\-time permanent position based in Barcelona, Spain and will require hybrid working in our Barcelona office, which is located next to Sagrada Familia (2 days per week in office, rest of week remote). This position requires weekday (Monday \- Friday) attendance with some scheduling flexibility available around core working hours. \#LI\-Onsite, \#LI\-Hybrid At Clarivate, we are committed to providing equal employment opportunities for all qualified persons with respect to hiring, compensation, promotion, training, and other terms, conditions, and privileges of employment. We comply with applicable laws and regulations governing non\-discrimination in all locations.