Overview
The Staff Officer (Data Science) role involves conducting advanced data analytics for Information Environment Assessment (IEA) activities, applying data science techniques to enhance IEA products and overseeing data analytics implementation.
Key Responsibilities
- Conduct hands-on data analysis and modeling in support of IE assessment, including data exploration, preparation, statistical analysis and the application of machine and deep learning and other advanced analytical techniques.
- Develop and apply advanced or novel analytical approaches to enhance IEA products, including the design of custom data processing pipelines, visualisations, models and rapid prototypes to test and operationalise new analytical concepts.
- Produce high-quality analytical outputs, including reports, briefings and visualisations with clear, evidence-based and actionable recommendations.
- Support the application of data, advanced analytics and AI in support of the IEA capability across Allied Command Operations (ACO) by developing and implementing analytical approaches, models and tools in line with established technical direction.
- Oversee the implementation of data analytics within the IEA branch, ensuring the effective application of tools, methodologies and analytical approaches, and supporting the use of commercially available data analytics tools through the provision of technical guidance and the promotion of best practices to analysts.
- Contribute to the quality, scope and operational relevance of Information Environment Assessments by applying rigorous analytical methods and critical judgement.
- Maintain awareness of emerging analytical methods, tools and data sources relevant to Information Environment Assessment and contribute to their practical application where appropriate.
- Undertake additional duties and assume other responsibilities as directed by the Chain Of Command.
Required Experience
- University Degree in statistics, applied mathematics, computer science, economics, operations research or related discipline (i.e., field with strong focus on statistical modelling and machine learning) and 4 years post related experience, or Higher Secondary education and completed advanced vocational training in that discipline leading to a professional qualification or professional accreditation with 6 years post related.
- Minimum of 4 years post-related experience relating to data science, analytics, AI or a related field in line with expertise and competencies outlined for this role.
- Experience of working with large and complex data sets, including both structured (e.g., relational databases, time-series data) and unstructured data (e.g., natural language, sensor data)
- Experience in data transformation, integration and analysis, including cleaning, pre-processing and feature engineering of structured and unstructured data for statistical modelling, machine learning and AI system development.
- Strong background in statistical modelling, machine learning and AI, including the applications of these techniques to real-world problems.
- Experience in developing custom analytical solutions, including the use of programming languages (e.g. Python), for data processing, visualisation and machine and deep learning.
- Experience in qualitative and quantitative data collection, processing and analysis, including working with audience research data (e.g., survey data)
- Demonstrated experience in using analytics and analytical tools to generate actionable insights in support of decision-making.
- Experience in developing reports and data visualisations, with the ability to communicate complex analytical findings as a clear, compelling and evidence-based manner.
Qualifications
University Degree in statistics, applied mathematics, computer science, economics, operations research or related discipline (i.e., field with strong focus on statistical modelling and machine learning) or Higher Secondary education and completed advanced vocational training in that discipline leading to a professional qualification or professional accreditation.
