Data Scientist

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.