Senior Data Scientist

Join our team as a Senior Data Scientist, where you will work across the data lifecycle in a fast-paced Agile environment. You will develop machine learning and data-driven solutions that support defensive cyber operations and operational decision-making. The role includes client-site work, flexible and remote working options, career development, training, and a competitive reward package. You will collaborate with multidisciplinary product teams, explore large datasets, communicate findings to stakeholders, and contribute to the development of innovative AI and machine learning capabilities.

• Concevoir, développer et déployer des solutions statistiques, perspicaces, d'IA et d'apprentissage automatique pour résoudre des défis opérationnels.
• Explorer de grands ensembles de données complexes pour identifier des tendances, des modèles et des informations exploitables.
• Collaborer avec des équipes multidisciplinaires pour transformer de grandes quantités de données en produits de données opérationnels fiables.

• The role requires a strong foundation in data science together with practical experience operating within modern data platforms, MLOps environments and software engineering workflows
• Experience using distributed data-processing and MLOps tools such as Spark, PySpark, MLflow, JupyterHub or equivalent technologies
• Practical experience with Git, Agile delivery and collaborative software-development workflows
• Candidates should typically bring at least three years of relevant professional experience, although applicants with less experience and strong evidence of capability will also be considered
• Understanding of data-product lifecycles, data quality, governance, reproducibility and auditable insightful workflows
• Strong Python and SQL skills, with experience developing production-quality insightful, statistical, AI and machine-learning solutions
• Experience working with large, complex, structured and unstructured datasets, including data preparation, exploratory analysis, feature engineering and model validation
• Effective collaboration within multidisciplinary teams, supported by strong problem-solving, documentation and critical-thinking skills
• Ability to translate operational or business needs into insightful solutions and communicate findings clearly to technical and non-technical stakeholders
• Advanced statistical modelling, experimental design, forecasting, anomaly detection, model optimisation or explainability
• Deployment and operation of machine-learning models, including monitoring, drift detection and performance management
• Awareness of modern lakehouse or enterprise data platforms and technologies such as Trino and Apache Iceberg
• Responsible AI or retrieval-augmented generation
• Experience in NLP, large language models, Generative AI, deep learning, graph analytics
• Delivery of data products or decision-support capabilities in secure, governed or operational environments
• Stakeholder engagement, workshop facilitation and presentation of insightful findings to senior audiences
• Curious, insightful and outcome-focused, with a commitment to technical excellence and continuous learning
• Motivated to deliver data products that create measurable user and mission impact
• Collaborative and comfortable working through complexity and ambiguity
• Able to balance innovation with operational reliability, governance and security
• Evidence of relevant continuing professional development
• A degree in data science, computer science, software engineering, mathematics, statistics, physics, engineering or another quantitative discipline, or equivalent professional experience
• A postgraduate qualification or recognised professional certification in data science, AI, machine learning, data engineering, cloud platforms, Agile delivery, Responsible AI or security is advantageous but not essential