Data Scientist

The Data Scientist will contribute to the development and modernization of WIPO’s statistical and analytical outputs, supporting the delivery of high-quality, transparent, and internationally comparable IP statistics. The role supports analytical and digital initiatives, applying advanced analytics and AI/ML to deliver actionable insights for Member States and senior management, focusing on strategies to increase the use of WIPO’s global IP systems.

Responsibilities

• Implement and enhance internal and external statistical reporting tools in line with the Division's standards, ensuring accessibility, transparency, and clarity in the interpretation of IP statistics.
• Build and maintain assigned web-based dashboards, data access platforms, and analytics pipelines, in collaboration with relevant WIPO sectors, to support monitoring, analysis and decision-making related to system usage and growth.
• Carry out defined analytical workstreams within statistical and data science projects, applying advanced analytical techniques, including machine learning, LLMs, and predictive modeling where appropriate, to help identify drivers, barriers and opportunities for increased uptake of WIPO services.
• Perform data analysis using relevant tools (e.g., SQL, R, Python) and translate results into actionable insights for Member States and senior management, including insights to inform policy, operational and growth-related decisions.
• Apply MLOps best practices for model development, deployment, monitoring, and reproducibility.
• Support projects across their lifecycle, including problem definition, metrics development, data extraction and manipulation, visualization, creation of analytical/statistical models and AI/ML solutions, and presentation of findings to stakeholders.
• Contribute to the development and modernization of statistical databases, data platforms, and analytics pipelines, ensuring secure storage, efficient retrieval, and accurate analysis.
• Apply and promote best practices in data management, MLOps, model governance, and analytics, supporting international comparability and high standards of IP statistical reporting.
• Contribute to the continuous improvement of internal systems and public-facing web products, enhancing usability and reliability of statistical information, including integration of AI-driven features where relevant.
• Contribute to the strategic and operational activities of the Division, including cross-sectional initiatives related to data integration, analytics platforms, innovation and digital transformation.
• Perform other related duties as required.

Requirements

• First-level university degree in statistics, mathematics, data science, computer science, economics or related discipline.
• At least six years of progressively responsible professional experience in the fields of data analytics, data science, machine learning or a related field.
• Experience making use of unit record databases to generate actionable intelligence that informs client decision making.
• Experience using statistical and econometric software and tools (e.g. STATA, Python, R and comparable analytical environments).
• Experience applying data science and machine learning techniques to large-scale statistical databases and data platforms.
• Experience in advanced data preparation, validation, analysis, modelling and quality assurance.
• Professional experience in the field of IP (desirable).
• Experience deploying and maintaining analytical models and data pipelines in production environments, including version control, monitoring and reproducibility practices (MLOps) (desirable).
• Excellent knowledge of written and spoken English.
• Good knowledge of other UN official languages (desirable).
• Good knowledge of data science and advanced analytical methods, including the application of machine learning techniques where appropriate, to support statistical analysis, trend analysis and forecasting.
• Excellent quantitative analytical and problem-solving skills, with the ability to interpret complex datasets and produce accurate, well-structured statistical outputs.
• Ability to understand and respond to client needs, uncover underlying reasons and trends using the available data, while effectively communicating complex findings in a clear and actionable manner to non-expert audiences to support informed decision making and drive business impact.
• Strong organizational, project and change management skills in a cross functional setting, with the ability to plan and manage assigned tasks independently, meet deadlines and ensure high standards of data quality and consistency.
• Ability to work effectively on own initiative and as a member of a team.
• Excellent communication and interpersonal skills, with the ability to establish and maintain effective working relationships in a multicultural environment, demonstrating sensitivity to and respect for diversity.
• Good knowledge of intellectual property (desirable).

Skills

• Data Analytics
• Data Science
• Machine Learning
• Statistical Analysis
• Econometric Software
• STATA
• Python
• Data Preparation
• Data Validation
• Data Modelling
• Quality Assurance
• MLOps principles
• Analytical Modeling
• Data Pipelines
• Quantitative Analysis
• Statistical Forecasting
• Project Management
• Change Management
• Client Needs Assessment

Languages

English