Data Scientist in Reading

Data Scientist

While professional experience and qualifications are key for this role, make sure to check you have the preferable soft skills before applying if required.

Are you passionate about pushing the boundaries of Machine Vision? We’re looking for a talented Data Scientist specialising in Machine Vision or Spatial Analysis to develop, train, and deploy advanced image and video detection models across EO, IR, near-IR, and multi-band data sources.

You’ll work at the forefront of deep learning and classical computer vision, designing solutions for challenging real-world applications including small and distant object detection, multi-modal fusion, and real-time performance optimisation.

Key Responsibilities

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Design, train, and optimise detection and classification models using deep learning and classical computer vision techniques.

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Manage and prepare large-scale imagery datasets, including labelling, augmentation, and quality checks.

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Develop algorithms for multi-spectral and fused EO/IR/near-IR data.

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Validate, benchmark, and refine models for deployment in real-time or embedded environments.

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Collaborate with engineering teams to integrate, deploy, and maintain production-grade vision models.

Requirements

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Strong expertise in machine vision, including CNNs, transformer-based architectures, and classical CV methods (OpenCV, scikit-image).

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Proficiency in Python and key ML/vision libraries (PyTorch, TensorFlow, NumPy, SciPy, scikit-learn).

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Experience designing models for detection/classification (YOLO, Faster R-CNN, RetinaNet, ViT, EfficientNet).

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Hands-on experience with imagery across EO, IR, and/or multi-band datasets.

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Solid understanding of machine learning fundamentals, training workflows, and evaluation metrics.

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Master’s/Ph.D. in Computer Vision, Machine Learning, Data Science, Applied Mathematics, or related field, plus 2–5 years’ relevant experience.

Soft Skills

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Strong analytical mindset with exceptional problem-solving abilities. xiskglj

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Clear communication and documentation skills.

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Proactive, collaborative, and comfortable working in a fast-paced, research-driven environment