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# Data Scientist (Electromagnetic Environment)

- **Company:** Metrea Management Llc
- **Location:** London, UK
- **Contract:** Permanent contract
- **Skills:** Data Analysis, Automation of Tests, Monitoring of Systems, Python (Programming Language), Machine Learning, Tensorflow, Scientific Computating, Signal Processing, Convolutional Neural Networks, Information Technology, Modeling and Simulation, Machine Learning Operations, Software Version Control
- **Published:** July 26, 2026
- **Apply:** https://uk.indeed.com/viewjob?jk=2375a7f8c6d60acd

## About the Role

* A post-doctoral degree in a quantitative field such as Physics, Engineering, Mathematics, Computer Science, Statistics, or a related STEM discipline, or equivalent professional experience supported by a Master's degree
 * Familiarity with modern approaches such as CNNs, Transformers, autoencoders, self-supervised learning, probabilistic modelling, or simulation-driven learning
 * Strong programming capability in Python, including experience with scientific computing, machine learning frameworks, and data analysis libraries
 * Experience applying data science, machine learning, or advanced analytics to electromagnetic or related operational problem sets
 * Ability to design rigorous experiments, evaluate model and algorithm performance, and translate findings into clear technical recommendations
 * Excellent communication skills, with the ability to explain complex ML, RF, statistical, and engineering concepts to technical and non-technical audiences
 * A collaborative mindset, strong technical curiosity, and the ability to work effectively in a fast-paced, mission-focused environment, The employee will have the legal right to work in the UK and will be able to produce right to work documentation.

## Description

In this role, you will apply machine learning, data science, and advanced analytical techniques to complex challenges across the electromagnetic environment. Working within Metrea's Decision Science Laboratory (DESLAB) and automated Solution Engine, you will design, test, and deploy ML-enabled capabilities that go beyond traditional signal processing approaches. This includes exploring the potential of methods such as Transformers, self-supervised learning, probabilistic modelling and simulation-driven learning approaches for electromagnetic sensing and exploitation. You will be successful if you are comfortable moving between research, experimentation, and operational delivery, turning ambiguous Defence and Aerospace problems into robust technical solutions that can be tested, explained, and deployed in real-world settings., * Translate operational requirements into technical solutions, working closely with cross-functional teams across decision science, electromagnetic simulation, waveform design, engineering, operations, hardware, and aerial systems

 * Apply machine learning, data science, and RF-aware analytical techniques to electromagnetic, problem sets, including spectrum classification, emitter detection, anomaly detection and signal characterisation
 * Explore and develop modern approaches for electromagnetic sensing and exploitation, including convolutional neural networks, transformers, autoencoders, graph-based methods or probabilistic approaches for uncertainty-aware decision-making
 * Design and conduct experiments to assess new algorithms and techniques
 * Develop proof-of-concept capabilities and support the deployment of selected approaches into operational environments
 * Liaise with forward-deployed teammates to understand real-world constraints, user needs, data limitations, environmental effects, and deployment considerations
 * Build reliable analytical workflows using appropriate MLOps, and cloud-based practices, including version control, experiment tracking, automated testing, model monitoring, and scalable compute infrastructure
 * Communicate complex technical concepts for no-technical users clearly through reports, demonstrations, briefings, and workshops
 * Mentor junior team members and help foster a collaborative, innovative, and technically rigorous environment, while staying current with emerging developments


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