Job Title

Few&Far has teamed up with a Series A startup looking to get their Series B late 2025/early 2026;Senior Data ScientistWe are seeking a 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 ResponsibilitiesContribute 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 Experience5+ 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 RequirementsAdvanced 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.