Data Scientist
Location: London (3-4 days per week on-site)
Type: Permanent
Clearance: DV required | UK nationals only
Salary: up to £70,000 gross per annum
The Opportunity A leading organisation within the digital defence and security space is looking to bring in a Data Scientist to support the delivery of secure, data-driven solutions across complex government programmes.
You’ll be part of a high-performing team working at the forefront of data exploitation, advanced analytics, and machine learning, helping to deliver real-world impact across critical environments. The role offers strong exposure to varied datasets, evolving problem sets, and the opportunity to shape solutions end-to-end.
What You’ll Be Doing: You’ll play a key role in designing and delivering data-driven solutions, working across the full machine learning lifecycle from early exploration through to production deployment. Operating within a collaborative, multi-disciplinary environment, you’ll combine strong technical capability with practical delivery, helping translate complex data into actionable insights. This is a hands‑on role where you’ll work closely with analysts, engineers, and stakeholders, developing models, integrating them into real systems, and continuously improving performance in live environments.
Responsibilities:
- Designing, developing, and testing data pipelines to collect, integrate, and prepare data for analytics and ML use cases.
- Analysing complex datasets to identify trends, patterns, and actionable insights.
- Building, prototyping, and validating statistical and machine learning models.
- Taking ownership of ML solutions across the full lifecycle, from development through to deployment and optimisation.
- Deploying models into production environments and integrating them into wider systems.
- Monitoring model performance, identifying drift, and driving continuous improvement.
- Working closely with cross-functional teams to define requirements and enhance data‑driven capabilities.
- Communicating findings and recommendations to both technical and non-technical stakeholders.
- Applying data science techniques across varied datasets, including large-scale and unstructured sources.
- Leveraging tools and technologies such as Python, ELK stack, NiFi, APIs, and geospatial platforms.
- Supporting data exploitation use cases, including open-source and intelligence‑driven data sets.
- Ensuring solutions align with ethical standards, governance frameworks, and best practice.
- Providing technical guidance and mentoring where needed across the team.
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