Data Science and Analytics

<!–

Description

–>

The Department of Safeguards carries out the IAEA’s duties and responsibilities as the world’s nuclear inspectorate, supporting global efforts to stop the spread of nuclear weapons. The primary role of the Department is to develop and implement IAEA safeguards to ensure that there is no diversion of declared nuclear material from peaceful activities and no indications of undeclared nuclear material or activities in a State as a whole.

The Department comprises nuclear safeguards inspectors, responsible for carrying out inspections and verifications of all-safeguards relevant information for nuclear facilities in over 180 States; and technical staff responsible for a wide range of activities including: developing concepts and approaches for implementing safeguards; developing and maintaining safeguards equipment; providing analytical and laboratory services for sample analysis;  collecting, evaluating and analysing safeguards-relevant information; providing information and communication technology infrastructure and services; and providing programme coordination support.

The Division of Information Management (SGIM) implements state of the art methodologies and techniques for the collection, processing and analysis of a range of safeguards-relevant information, including declarations submitted by States, evaluations resulting from the analysis of samples or measurements collected during infield activities, and information from open sources, including nuclear trade-related data and satellite imagery. Staff perform data validation and complex information analysis and evaluation to support infield activities and provide key input to the State evaluation process.

Main Purpose

Are you passionate about data science and eager to apply your skills to real-world challenges in an international organization? The Safeguards Division of Information Management is seeking a data science and analytics intern with great analytical skills and strong interest in machine learning, particularly in the areas of large language models and generative AI. Join our team and contribute to the development of cutting-edge data science solutions.

As a data science and analytics intern, you will have the opportunity to work alongside experienced data scientists to support analysts and subject matter experts in the collection and validation of safeguards relevant information. This involves a wide range of tasks, including training and monitoring text classification models, ensuring explainability and robustness, while also exploring and leveraging emerging technologies.

Functions / Key Results Expected

As an intern within the Safeguards Division of Information Management, you will support the enhancement of analytical capabilities and be provided with a high level of professional development. Your tasks will include the following:

• Building rapid prototypes and proof of concepts to determine fit and usability
• Continuously improving machine learning models, including but not limited to text classification, information retrieval, and named entity extraction
• Interacting with business users to define the scope and business case
• Developing and applying technologies such as machine learning, and deep learning algorithms to enable advanced analytics product functionality
• Identifying valuable data sources and automating collection processes

Qualifications and Experience

• University degree in mathematics, computer science or a related field with a focus on data science or artificial intelligence.
• If you have the following attributes and meet the eligibility criteria, we would be very interested to hear from you:
• Demonstrated skills in analytic language Python
• Experience in machine learning methodologies (e.g. supervised and unsupervised learning, deep learning etc.) and understanding of large language model concepts
• Knowledge of popular machine learning libraries and frameworks, such as PyTorch and Hugging Face

Source: https://iaea.taleo.net/careersection/ex/jobdetail.ftl?job=TAL-SGIM20240313-002

<!—

<!–

–>