Senior Research Scientist: Data Science and Machine Learning AIP

BAE Systems Digital Intelligence
Chelmsford
1 week ago
Applications closed

Related Jobs

View all jobs

Senior Research Data Scientist

Senior Research Data Scientist: Customer-First AI & ML

Data Scientist (Mid - Senior Level)

Data Scientist

Data Scientist | The Christie NHS Foundation Trust

Modeller and Data Scientist

Senior Research Scientist: Data Science and Machine Learning AIP

Location: Great Baddow, UK • Hybrid working: 2 days onsite per week
Requisition ID: 121740 • Grade: GG11 • Referral Bonus: £5,000

BAE Systems Digital Intelligence is home to 4,500 digital, cyber and intelligence experts. We work across 10 countries to collect, connect and understand complex data, enabling governments, armed forces and commercial businesses to unlock digital advantage in demanding environments.

BAE Systems Digital Intelligence Innovation and Technology is seeking to recruit a senior researcher to join our rapidly expanding Data and Decision Support Capability. You should have a solid background in Machine Learning (ML) and/or statistical signal processing with excellent programming skills in Python and extensive experience with libraries and toolboxes to support efficient development. The right candidate will join our Advanced Information Processing (AIP) group, specializing in developing novel inference algorithms and applying AI/ML to sequential (time-series) data and decision making. The role offers the opportunity to work on AI/ML research topics for customers across space, defence, security and commercial sectors, as well as internal BAE Systems programmes, with opportunities to collaborate with Academic partners and grow technical research areas of interest.

The Data and Decision Support Capability has teams working across AI/ML areas such as AI/ML for RF, EW, radar, sonar, distributed sensing-processing, data fusion, reinforcement learning, agent-based ML, autonomy, ML for signal processing, edge ML, image analysis and computer vision, generative AI, deep learning, LLMs, knowledge graphs, NLP, graph ML and more. You will have the opportunity to work with colleagues in multi-disciplinary teams.

Typical Responsibilities
  • Lead technical delivery of projects, lead junior researchers. Prepare and deliver technical reports, technical proposals and supporting material
  • Lead novel research in given topic areas; collaborate with internal or external partners and/or UK universities
  • Develop prototypes and proof of concept demonstrators
  • Take ownership of tasks in projects and deliver to challenging standards
  • Work effectively on self-directed projects and as part of a project team
  • Present results to technical and non-technical audiences
  • Mentor junior staff working on related research topics
  • Publish and/or patent novel concepts and research findings where appropriate
Essential Knowledge, Skills And Experience
  • PhD or equivalent industry experience in a relevant discipline
  • Several years of expertise in applying AI/ML and/or statistical signal processing to sequential (sensor time-series) data and decision-making post-PhD
  • Experience in software development for proof of concept in Python
  • Experience with machine and deep learning frameworks: TensorFlow, PyTorch, scikit-learn, etc.

Of particular interest are candidates with experience in one or more of the following domains:

  • RF communications and CEMA
  • Electronic or Electromagnetic Warfare (EW)
  • Tracking and sensor data fusion
  • Radar signal processing
  • Acoustic data processing (including sonar)
  • Distributed sensing and processing
  • Autonomy
  • Human machine teaming
  • Space-domain Awareness (SDA)
  • Positioning, navigation, and timing
  • Pattern of life analytics
Why BAE Systems?

This is a place where you’ll be able to make a real difference. You’ll be part of an inclusive culture that values diversity of thought, rewards integrity and merit, and where you’ll be empowered to fulfil your potential. We welcome people from all backgrounds and encourage inclusive recruitment. If you have a disability or health condition that may affect your performance in certain assessment types, please speak to your recruiter about potential reasonable adjustments. Please note that many roles require security and export control checks, including Baseline Personnel Security Standard and possibly higher levels of National Security Vetting depending on the role.

Division overview: Capabilities. At BAE Systems Digital Intelligence, Capabilities is the engine that keeps the business moving forward and encompasses Engineering, Consulting and Project Management teams that design and implement defence solutions and digital transformation projects.

Referrals increase your chances of interviewing at BAE Systems Digital Intelligence by 2x. Get notified about new Senior Research Scientist jobs in Chelmsford, England, United Kingdom.


#J-18808-Ljbffr

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Maths for Machine Learning Jobs: The Only Topics You Actually Need (& How to Learn Them)

Machine learning job adverts in the UK love vague phrases like “strong maths” or “solid fundamentals”. That can make the whole field feel gatekept especially if you are a career changer or a student who has not touched maths since A level. Here is the practical truth. For most roles on MachineLearningJobs.co.uk such as Machine Learning Engineer, Applied Scientist, Data Scientist, NLP Engineer, Computer Vision Engineer or MLOps Engineer with modelling responsibilities the maths you actually use is concentrated in four areas: Linear algebra essentials (vectors, matrices, projections, PCA intuition) Probability & statistics (uncertainty, metrics, sampling, base rates) Calculus essentials (derivatives, chain rule, gradients, backprop intuition) Basic optimisation (loss functions, gradient descent, regularisation, tuning) If you can do those four things well you can build models, debug training, evaluate properly, explain trade-offs & sound credible in interviews. This guide gives you a clear scope plus a six-week learning plan, portfolio projects & resources so you can learn with momentum rather than drowning in theory.

Neurodiversity in Machine Learning Careers: Turning Different Thinking into a Superpower

Machine learning is about more than just models & metrics. It’s about spotting patterns others miss, asking better questions, challenging assumptions & building systems that work reliably in the real world. That makes it a natural home for many neurodivergent people. If you live with ADHD, autism or dyslexia, you may have been told your brain is “too distracted”, “too literal” or “too disorganised” for a technical career. In reality, many of the traits that can make school or traditional offices hard are exactly the traits that make for excellent ML engineers, applied scientists & MLOps specialists. This guide is written for neurodivergent ML job seekers in the UK. We’ll explore: What neurodiversity means in a machine learning context How ADHD, autism & dyslexia strengths map to ML roles Practical workplace adjustments you can ask for under UK law How to talk about neurodivergence in applications & interviews By the end, you’ll have a clearer sense of where you might thrive in ML – & how to turn “different thinking” into a genuine career advantage.

Machine Learning Hiring Trends 2026: What to Watch Out For (For Job Seekers & Recruiters)

As we move into 2026, the machine learning jobs market in the UK is going through another big shift. Foundation models and generative AI are everywhere, companies are under pressure to show real ROI from AI, and cloud costs are being scrutinised like never before. Some organisations are slowing hiring or merging teams. Others are doubling down on machine learning, MLOps and AI platform engineering to stay competitive. The end result? Fewer fluffy “AI” roles, more focused machine learning roles with clear ownership and expectations. Whether you are a machine learning job seeker planning your next move, or a recruiter trying to build ML teams, understanding the key machine learning hiring trends for 2026 will help you stay ahead.