Data Scientist

Clarivate•Belgrade, ME

12d•Hybrid

About The Position

We are looking for a Data Scientist to join the Institute for Scientific Information (ISI), part of the Research & Analytics business unit in Clarivate. This is a rare opportunity to combine deep technical work with real world impact on the integrity, evaluation, and future direction of science. 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. In this role, you will work with senior members of the team to 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.

Requirements

Minimum 2 years of professional experience including 2+ years of experience with the Python data analysis and data science ecosystem
2+ years of experience with SQL
2+ years of experience with data visualization platforms (Power BI, Tableau or similar)
1+ year of experience with use of existing LLMs, topic modelling, network analysis or text mining
Bachelor's Degree and/or equivalent in computer science, software engineering, or a related field
Proficiency in English

Nice To Haves

Awareness of academic research and understanding of the research ecosystem
Experience of analysis of data and content in Web of Science, InCites or similar platforms

Responsibilities

Analyze large-scale datasets using statistical models and machine learning techniques, including structured data (citation metadata, affiliations, funding records) and unstructured data (titles, abstracts, patents), to create actionable insights for research evaluation and intelligence.
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.
Work with senior ISI colleagues to translate business challenges and requirements into data science solutions.
Stay engaged and adapt to the latest trends, tools, and techniques in data science to continuously improve your analytical capabilities.
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.