The Information Management Section (INMA) is responsible for the establishment and maintenance of the mechanisms required to collect, collate and analyse nuclear security related information required for the effective implementation of activities to strengthen the international nuclear security framework. The Section is responsible for managing and maintaining the Incident and Trafficking Database and related information, as well as the system to develop and coordinate the implementation of Integrated Nuclear Security Support Plans. For this purpose, it liaises with other international organizations and Member States to enhance cooperation in and increase the outreach of nuclear security information. The Section is also responsible for managing and maintaining the information technology systems necessary for implementing the work of the Division and providing for information exchange through internal and external information portals. Additionally, the Section is responsible for managing and implementing the programme of activities for raising States' awareness of the threat of cyber-attacks, and their potential impact on nuclear security. The Section is also responsible for implementing arrangements to maintain the confidentiality of sensitive information.
Main Purpose:
Under the supervision of the Information Management Section Head and in close collaboration with the Analytics and IT Teams, as well as the Programme Management Officer overseeing the results-based management portfolio, the Consultant - Data Scientist will be instrumental in developing and refining proof of concepts (PoCs) for the division's initiatives in Data Science, Machine Learning (ML), and Artificial Intelligence (AI). This role focuses on safe, secure, and trustworthy AI, integrating a results-based approach and a need for structured analytics. Responsibilities include identifying high-value use cases, collaborating with stakeholders, and creating data-driven prototypes to demonstrate the potential of AI/ML technologies for enhancing nuclear security processes and decision-making. The Consultant will offer technical expertise to promote the use of advanced analytical tools and methodologies, aiming to make significant progress towards the division's operational and strategic objectives in implementing an evidence- and results-driven Nuclear Security Programme.
Functions / Key Results Expected:
Develop Analytical Tools: Identify valuable data sources relevant to nuclear security and develop tools for automated data collection, integration, and analysis.
Build Proof of Concepts (PoCs): Leverage machine learning models and deep learning algorithms to construct PoCs that demonstrate advanced functionalities, such as anomaly detection, pattern recognition, and predictive modeling, to support informed decision-making processes.
Monitor Model Performance: Design and implement processes and tools to continuously monitor the performance and accuracy of analytical models, identifying areas for improvement and recommending optimizations.
Contribute to Standards Development: Provide guidelines and standards for the ethical and effective use of data science tools and AI/ML technologies within the Division.
Provide Training and Knowledge Transfer: Deliver internal training sessions on data science approaches, tools, and best practices to enhance the analytical capabilities of the Division.
Knowledge, Skills and Abilities:
Required -
Data Modelling
Data Analysis
Semantics Analytics and Visualization
Qualifications and Experience:
University degree or Advanced university degree in Data Science, Computer Science, Information Systems, or a related field. Advanced degrees or certifications in AI/ML are highly desirable.
Minimum of three years of hands-on experience in data science or a related field, with a proven track record of developing and implementing ML models and data-driven solutions in real-world applications, ideally within a security or regulated environment.
Technical Proficiency: Extensive practical experience in using data science tools and programming languages (Python, R), along with proficiency in AI/ML frameworks (TensorFlow, PyTorch, scikit-learn).
Strong Analytical and Problem-Solving Skills: Ability to analyze complex problems, identify patterns, and develop effective solutions through data-driven insights.
Excellent Communication and Collaboration: Outstanding oral and written communication skills in English, with the ability to effectively translate technical concepts for diverse audiences. Knowledge of other IAEA languages is an asset.
