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Organizational Setting
The Division of Information Technology provides support to the IAEA in the field of information and communication technology (ICT), including information systems for technical programmes and management. It is responsible for planning, developing, and implementing an ICT strategy, for setting and enforcing common ICT standards throughout the Secretariat and for managing central ICT services. The IAEA's ICT infrastructure comprises hardware and software platforms, and cloud and externally hosted services. The Division has implemented an IT service management model based on ITIL (IT Infrastructure Library) and Prince2 (Projects in a Controlled Environment) best practices.
Main Purpose
IAEA aims to implement its inaugural Data Strategy, focusing on creating a data catalogue, and identifying and analysing data use cases across all business programs. This initiative is pivotal for strengthening our data governance process and augmenting the business impact of our data assets. Concurrently or in a sequence, a project on an assessment of our Data Integration Architecture and Governance is being undertaken, aiming for mutual reinforcement of insights between the two projects.
Functions / Key Results Expected
1. Under the supervision of the Chief Data Officer (CDO), align data strategies with organizational objectives, ensuring a cohesive approach to data-driven decision-making. Utilize statistical and computational techniques to extract valuable insights from large and complex datasets. Creates, implements, and deploys AI solutions in business environments, considering scalability, reliability, and security.
2. Work closely with data engineers/architects to define data requirements, ensuring comprehensive accessibility for analysis. Apply advanced analytical methods, machine learning, and deep learning algorithms to identify intricate patterns and trends within the data. Perform meticulous data cleaning, conduct statistical analysis, and create visualizations to effectively communicate complex findings to diverse stakeholders.
3. Support decision-making processes by providing actionable, data-driven recommendations derived from thorough analyses Act as an explorer, conducting exploratory data analysis, cleaning, and transformation operations to uncover nuanced trends and patterns Develop statistical predictive models using data mining techniques, including linear and logistic regression, neural networks, decision trees, and experimental design.
4. Design and develop big data applications for implementing predictive analytics and machine learning algorithms, driving valuable insights from available data Utilize statistical programming languages (e.g., R or Python) and database querying languages proficiently.
5. Interpret and consolidate large amounts of information into actionable recommendations, assist CDO in effectively communicating results and implications to business stakeholders. Establishes the governance of data and algorithms used for analysis, analytical applications, and automated decision-making.
Knowledge, Skills and Abilities
Assets
Qualifications and Experience
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Advanced University Degree in Computer Science, Data Management, Data Analytics, Statistics or Engineering or related field / (or University Degree with two additional years of experience may be considered in lieu of Advanced University Degree.)
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Minimum of five years of experience with AI data science, ML engineering, or data analytics or a related field.
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Minimum of two years of experience designing and implementing AI solutions with a focus on machine learning, recommendation systems, pattern recognition, NLP, or data mining
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Proven project experience with programming languages such as SQL, Python, and R for data manipulation and analysis
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Proven project experience with data analysis and visualization tools such as Tableau, Power BI, and Excel
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Expert knowledge of statistical analysis techniques and concepts for both descriptive and inferential statistics
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Knowledge of data visualization best practices to effectively communicate insight.
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Strong analytical and problem-solving skills to interpret complex datasets and generate meaningful insights.
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Familiarity with data modelling and data warehousing concepts
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Ability to work with large datasets through data cleaning, preprocessing, and transformation techniques.
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Excellent communication skills to convey complex data findings to both technical and business executives.
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Attention to detail and ability to maintain data accuracy and integrity.
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Fluency in English. Knowledge of the other IAEA official languages is an asset.
Remuneration
The remuneration for this consultancy is a daily fee of up to a maximum of € 340, based on qualifications and experience. In case duty travel is required within the assignment, a daily subsistence allowance (DSA) and travel costs are provided. Health coverage and pension fund are the responsibility of the incumbent.
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