FYLD is looking for a Senior Data Scientist reporting into our Director of Engineering. This is a key hire for the business, as we continue to invest in our AI and data capabilities, which will increasingly underpin the value we can offer customers and our long-term roadmap. We need an experienced AI leader who can contribute to the broader product and company strategies, hire and develop an excellent team, and institute effective ways of working that maximise the results we can deliver for our customers.
FYLD has strong traction in the market and a healthy sales pipeline based on the productivity gains that can be realised from digitising processes for workers in the field. However, we are just scratching the surface of the value that we can unlock for our customers. By investing further in our AI capabilities, we can deliver even more value for customers, for example, predicting and preventing delays and site stoppages, by forecasting job durations to enable dynamic scheduling, while also deepening our competitive moat. The Senior Data Scientist will lead this drive to build our AI capabilities and translate this into products we can commercialise.

Key responsibilities include:

• Contributing to the long-term product vision
• Build a technology roadmap for AI that allows us to deliver this vision
• Building computer vision algorithms for tasks such as object detection, image segmentation, and scene understanding.
• Work closely with data engineers to improve data quality, labelling efficiency, and model accuracy
• Work closely with ML engineers to productise the AI models
• Ensure customers are successful in their use of our AI functionality

KEY EXPERIENCE:

• At least five years of experience in frameworks such as PyTorch and Tensorflow
• Two years of experience in object detection models, including but not limited to YOLO, Faster R-CNN, and VIT
• Experience in training, fine-tuning, quantisation, and deploying computer vision models in production
• Apply data augmentation, transfer learning, and hyperparameter tuning to optimise model performance on complex datasets
• Expertise in implementing hybrid search and retrieval-augmented generation (RAG) techniques
• Solid understanding of Large Language Models, including how to apply multi-modal models and when to apply prompt engineering and fine-tuning.
• Deployment and Cloud-based services - AWS, GCP, Docker, Linux
• Experience deploying ML models to edge devices with necessary optimisations

ADDITIONAL REQUIREMENTS:

• Advanced degree in Computer Science, Statistics, Data Science or equivalent
• Experience building and commercialising ML models
• Knowledge of the ML workflow, spanning from annotation, model training, model serving, scoring, pre/post processing, productionisation and feedback capture
• Knowledge of data ecosystems and tools, spanning from data ingestion, data engineering, data quality, data orchestration, and data privacy considerations and governance
• Data-informed - highly analytical thinker and structured problem-solver
• Demonstrates initiative while collaborating effectively with others to drive solutions forward
• Stakeholder management - ability to influence and advise key stakeholders at all levels across the organisation
• Operational execution - can run the processes and culture needed to deliver value from data and analytics teams reliably
• Comfortable working with ambiguous or evolving requirements, with a proactive and adaptable approach
• Experience in testing and validating non-deterministic systems

• Contributing to the long-term product vision
• Build a technology roadmap for AI that allows us to deliver this vision
• Building computer vision algorithms for tasks such as object detection, image segmentation, and scene understanding.
• Work closely with data engineers to improve data quality, labelling efficiency, and model accuracy
• Work closely with ML engineers to productise the AI models
• Ensure customers are successful in their use of our AI functionalit