Data Scientist

Company: BAE Systems Digital Intelligence
Apply for the Data Scientist
Location: Frimley
Job Description:

Location

UK, Europe & Africa : UK : Frimley

South of England – 4-5 days per week based on client site.

About The Role

We are looking for a Data Scientist to join our Digital Defence Services team following continuous growth and success. Within Digital Defence Services, we are a critical partner to the UK Ministry of Defence in adopting secure digital solutions that enable multi-domain integration and data exploitation. Positioned within a thriving Digital Defence Services Business Unit and part of a wider vibrant Security Consulting Community, you will be supported to learn, develop and progress within the organisation.

Core Duties

  • Design, develop, and test solutions to collect, integrate, and prepare data for advanced analytics and machine learning applications.
  • Analyse complex datasets to uncover trends, patterns, and actionable insights that drive business or operational outcomes.
  • Build, prototype, and evaluate statistical and machine learning models to solve real-world problems, testing feasibility and estimating impact before full deployment.
  • Engineer and implement ML-based solutions, owning the full lifecycle – from model development and deployment to monitoring and iteration.
  • Deploy models into production environments, handling the integration and operationalisation of ML within wider systems and applications.
  • Continuously evaluate and monitor model performance, identifying degradation, performance gaps, or opportunities for optimisation.
  • Collaborate closely with data analysts, engineers, and other stakeholders to define new tools, enhance workflows, and support innovation across teams.
  • Communicate findings, recommendations, and model outcomes to both technical and non-technical audiences through visualisation and data storytelling.
  • Research emerging AI/ML techniques to stay ahead of the curve and identify new opportunities to enhance current systems.
  • Ensure all data science and ML practices adhere to relevant ethical standards, policies, and governance frameworks.
  • Provide technical guidance and mentorship on ML implementation across cross‑functional teams.

Data Science and Analytics

  • Use and design of algorithms to extract meaningful, actionable insight from a variety of datasets. Develop, test, and deploy tooling across technologies such as Elastic, Logstash, Kibana (ELK), Ni‑Fi, Python, geospatial intelligence software and APIs from commercial/open‑source providers.
  • Conduct exploratory analysis of datasets to address a range of client problem sets.

Open‑Source Intelligence and Data Exploitation

  • Work with a range of datasets in support of open‑source intelligence objectives, applying techniques to improve customer outcomes and highlight dataset shortcomings.
  • Attend training to improve tradecraft, techniques, and investigative methods.
  • Have a strong foundation in data science, analytics or machine learning with hands‑on experience delivering models that solve practical problems and deliver measurable impact.
  • Be comfortable working across the full machine learning lifecycle – from exploratory data analysis and model prototyping to production deployment, integration, and ongoing monitoring.
  • Be proficient in Python and its data/ML ecosystem (pandas, scikit‑learn, PyTorch, TensorFlow) and apply statistical and machine learning techniques confidently in real‑world settings.
  • Have deployed models into live systems and understand how to make ML operational – whether that involves APIs, application integration or containerisation tools such as Docker.
  • Actively monitor the performance of deployed models, using experience in identifying drift, re‑training triggers or optimisation opportunities.
  • Stay current with the latest advancements in machine learning and AI and enjoy applying new methods or tools to improve systems and outcomes.
  • Be aware of ethical and governance considerations when deploying machine learning at scale (bias, fairness, explainability, compliance) and incorporate these into your work.
  • Communicate complex technical work into clear insights and recommendations, adapting the message for both technical and non‑technical stakeholders.
  • Work in cross‑functional teams, contributing expertise while collaborating with analysts, engineers, product teams, and decision‑makers.
  • Be self‑motivated, solution‑oriented and take ownership of work from scoping to production‑ready delivery.

Due to the nature of our business and requirements of this role, you will need to hold a MoD/Partner DV and be a UK National.

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Posted: May 25th, 2026