Senior Data Scientist
Few&Far
- London, England, United Kingdom
- London, England, United Kingdom
À propos
Senior Data Scientist
to join our growing team, reporting directly to the Director of Engineering. This is a critical hire as we continue to invest in our AI and data capabilities to enhance the value we offer to customers and shape our long-term product roadmap. This role is ideal for an experienced AI leader who thrives in a fast-paced environment, can contribute to strategic direction, build and mentor a high-performing team, and implement effective processes that drive tangible outcomes for customers. With strong traction in the market and a growing customer base, we are in an exciting phase of growth. Our current solutions offer significant productivity gains by digitising field operations — yet we believe this is just the beginning. By deepening our investment in AI, we aim to unlock new opportunities, such as predicting delays, preventing site stoppages, and enabling dynamic scheduling. The Senior Data Scientist will spearhead this effort — building advanced AI capabilities and transforming them into scalable, commercial products. Key Responsibilities Contribute to the long-term product vision and strategic direction. Develop an AI technology roadmap aligned with business goals. Build and deploy computer vision models (e.g., object detection, image segmentation). Collaborate with data engineers to improve data quality, labelling processes, and model performance. Work with ML engineers to productionise AI models effectively. Ensure customer success and adoption of AI-driven features and insights. Required Experience 5+ years working with deep learning frameworks such as
PyTorch
and
TensorFlow . 2+ years of experience in object detection models, including
YOLO ,
Faster R-CNN , and
ViT . Proven track record of training, fine-tuning, quantising, and deploying computer vision models in production. Expertise in
data augmentation ,
transfer learning , and
hyperparameter tuning
for complex datasets. Strong understanding of
hybrid search
and
retrieval-augmented generation (RAG)
techniques. Solid experience with
Large Language Models (LLMs) , including multi-modal models and applying
prompt engineering
and
fine-tuning . Experience deploying models via
cloud platforms
(AWS, GCP) and using
Docker ,
Linux , and
edge device optimisation . Additional Requirements Advanced degree in
Computer Science ,
Statistics ,
Data Science , or a related field. Proven experience building and commercialising machine learning models. Deep knowledge of the ML lifecycle: data annotation, model training, serving, scoring, productionisation, and feedback loops. Understanding of modern
data ecosystems
and tools across ingestion, engineering, quality, orchestration, and governance. Strong analytical and structured problem-solving skills. Proactive, collaborative, and comfortable navigating ambiguity. Ability to influence and communicate effectively with stakeholders across technical and business teams. Operational excellence in building scalable processes and culture around AI and analytics delivery. Experience in testing and validating non-deterministic systems. Seniority level
Seniority level Mid-Senior level Employment type
Employment type Full-time Job function
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Compétences linguistiques
- English
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