Principal Data Scientist

About this role

We are seeking highly skilled and experienced individuals to fill Principal Data Scientist roles within the ASIS Data Science and Artificial Intelligence Section. Data Scientists in ASIS work directly with client areas to make the best use of ASIS's unique data assets and achieve operational impact. They implement complex analytics and train and deploy machine learning models on premises and at the edge to enrich data and find the right information as quickly as possible. A genuinely agile approach combined with strong governance has made ASIS a leader in the adoption and development of artificial intelligence and data analytics. Principal Data Scientists will work with the Director of Data Science and Artificial Intelligence to provide technical leadership and ensure that ASIS maintains its position in this field. ASIS leverages the wide world of open-weight and proprietary AI models together with open-source software. We supplement this with our own research & development to deliver the bespoke tools required for the ASIS mission. Among our core languages are Python, Scala, Rust and TypeScript. Our toolset includes PyTorch, Tensorflow, MLFlow, Transformers, uv, Podman, FastAPI, Apache Spark, Apache Hadoop, Apache Solr, and Git. We leverage structured and unstructured data, including geospatial and multilingual data sets of varying quality. Ideal candidates will be extraordinarily innovative, self-motivated and keen to use these toolsets to craft new systems that are simply not found in any other organisation. An EL2 Principal Data Scientist is expected to have substantial experience and industry leading technical expertise in one or more data science or machine learning domains. They occupy positions of technical leadership , which may include management responsibilities, within the Data Science and Artificial Intelligence Section. As member of the Data Science and Artificial Intelligence leadership team you will: • Take a leading role in the development and implementation of the Data Science and AI strategy in alignment with ASIS’s mission and priorities. • Provide leadership within a growing Data Science and AI team; setting research and development priorities and leading their development, providing technical guidance, mentoring your colleagues and building solutions. • Engage with customers to identify potential operational benefits from the application of data science, including identifying relevant data and analytic opportunities and then taking ownership of the implementation of work to realise operational impact. • Collaborate with other technologists to build and maintain best practices for ML model training, storage, and deployment. • Represent ASIS in external fora and collaboration related to data science and artificial intelligence. • Act as a leader to foster a data driven culture across the organisation and support business areas to achieve operational outcomes. Core skills We encourage applicants with the following skills and attributes to apply: • Extensive practical experience and research in one or more of the following fields; complex data analytics, computer vision, natural language processing, large language models (LLMs) and other transformer based deep learning architectures, statistical modelling, probabilistic record linkage, distributed computing, graph/network analysis, orchestration and deployment of AI & ML models on GPU infrastructure at scale. • A Principal Data Scientist is expected to demonstrate industry leading subject matter expertise in at least one of the fields above. • Proficiency in relevant programming languages such as Python, R, Scala, or Rust, especially Python. • Strong leadership, mentoring, communication, and stakeholder management skills. Education and qualification requirements The following education, qualifications and/or experience will be highly regarded: • Proven experience in a senior data science practitioner or technical director role, with a strong track record of building innovative data capabilities. • Advanced degree or equivalent experience in data science, computer science, mathematics, statistics, physical sciences or a related field. Experience in the following would be beneficial, but not essential: • An understanding of the intelligence cycle and the role of data science in supporting intelligence operations. • Previous experience in the National Intelligence Community.