Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Senior Data Scientist

FYLD
Manchester
3 weeks ago
Create job alert

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


Experience

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


Location

This role is remote within the UK, with a commitment to commute to London for face-to-face meetings. This is a full-time role.


Competitive salary with benefits that include:

Private health insurance

Private dental cover

Pension scheme

Annual performance bonus

Death in service cover

Commute expensed


Application process

If you’re interested in this role, please email your CV to

Please do not reach out directly to the individuals mentioned directly on this document.


We won’t respond to emails from recruiters.


About FYLD

FYLD is the category creating, AI driven, field work execution platform for the infrastructure industry. We enable the world’s most progressive infrastructure companies to leverage real time data to transform their ways of working in the field. Our mission is to power productivity, safety, and efficiency in field teams around the world to meet the challenges of our times, including skilled labour shortages, regulatory cost pressures, zero harm to employees and sustainability.

At its core, our product has an app for field workers which is connected to a web-app for their remote managers and other back office functions. The app facilitates data collection in the field which is surfaced in real time to remote managers, as well as driving more efficient workflows for the worker (both on and offline through investment in edge-AI). For our remote managers, our increasingly intelligent web-app enables them to prioritise job sites to focus on, as well as process redesign based on deep data insights from the large data sets we collect on what it actually takes to complete processes in the field, and organisational challenges to support these processes being carried out efficiently.


Founded in 2020 as a partnership between Ontario Teachers’ Pension Plan, consultancy BCG X and major UK gas distributor SGN, FYLD has expanded rapidly as an innovator in the infrastructure sector, where software companies have yet to deploy ‘field fit’ solutions at scale, inhibiting effective utilisation. FYLD is now used by over 100 organisations across five different continents and with revenues forecast to 2X in 2024.


To date FYLD has raised £27m, and will raise its Series B in late 2025 to early 2026.


Inclusivity

At FYLD, we welcome everyone regardless of their background, race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, etc. We nurture an inclusive work environment and are committed to ensuring equal opportunity in employment for qualified persons with disabilities.

In addition, we have implemented a flexible way of working which we believe enables teams and individuals to do their best work, regardless of where they’re based. While we value in-person collaboration and know a change of scenery and quiet space to work is welcomed from time to time, we also appreciate and understand that the world of work has changed.

All offers of employment are contingent upon an individual’s ability to secure and maintain the legal right to work at the company.

We know that innovation thrives on product teams where diverse points of view come together to solve hard problems in ways that are just now possible. As such, we explicitly seek people that bring diverse life experiences, diverse educational backgrounds, diverse cultures, and diverse work experiences.

Please be prepared to share with us how your perspective will bring something unique and valuable to our product teams.

Related Jobs

View all jobs

Senior Data Scientist - Financial Services - Outside IR35

Senior Data Scientists

Senior Data Scientist

Senior Data Scientist

Senior Data Scientist

Senior Data Scientist

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

The Future of Machine Learning Jobs: Careers That Don’t Exist Yet

Machine learning (ML) has become one of the most powerful forces reshaping the modern world. From voice assistants and recommendation engines to fraud detection and medical imaging, it underpins countless applications. ML is no longer confined to research labs—it powers business models, public services, and consumer technologies across the globe. In the UK, demand for machine learning professionals has risen dramatically. Organisations in finance, retail, healthcare, and defence are embedding ML into their operations. Start-ups in Cambridge, London, and Edinburgh are pioneering innovations, while government-backed initiatives aim to position the UK as a global AI leader. Salaries for ML engineers and researchers are among the highest in the tech sector. Yet despite its current importance, machine learning is only at the beginning of its journey. Advances in generative AI, quantum computing, robotics, and ethical governance will reshape the profession. Many of the most vital machine learning jobs of the next two decades don’t exist today. This article explores why new careers will emerge, the roles likely to appear, how today’s roles will evolve, why the UK is well positioned, and how professionals can prepare now.

Seasonal Hiring Peaks for Machine Learning Jobs: The Best Months to Apply & Why

The UK's machine learning sector has evolved into one of Europe's most intellectually stimulating and financially rewarding technology markets, with roles spanning from junior ML engineers to principal machine learning scientists and heads of artificial intelligence research. With machine learning positions commanding salaries from £32,000 for graduate ML engineers to £160,000+ for senior principal scientists, understanding when organisations actively recruit can dramatically accelerate your career progression in this pioneering and rapidly evolving field. Unlike traditional software engineering roles, machine learning hiring follows distinct patterns influenced by AI research cycles, model development timelines, and algorithmic innovation schedules. The sector's unique combination of mathematical rigour, computational complexity, and real-world application requirements creates predictable hiring windows that strategic professionals can leverage to advance their careers in developing tomorrow's intelligent systems. This comprehensive guide explores the optimal timing for machine learning job applications in the UK, examining how enterprise AI strategies, academic research cycles, and deep learning initiatives influence recruitment patterns, and why strategic timing can determine whether you join a groundbreaking AI research team or miss the opportunity to develop the next generation of machine learning algorithms.

Pre-Employment Checks for Machine Learning Jobs: DBS, References & Right-to-Work and more Explained

Pre-employment screening in machine learning reflects the discipline's unique position at the intersection of artificial intelligence research, algorithmic decision-making, and transformative business automation. Machine learning professionals often have privileged access to proprietary datasets, cutting-edge algorithms, and strategic AI systems that form the foundation of organizational competitive advantage and automated decision-making capabilities. The machine learning industry operates within complex regulatory frameworks spanning AI governance directives, algorithmic accountability requirements, and emerging ML ethics regulations. Machine learning specialists must demonstrate not only technical competence in model development and deployment but also deep understanding of algorithmic fairness, AI safety principles, and the societal implications of automated decision-making at scale. Modern machine learning roles frequently involve developing systems that impact hiring decisions, financial services, healthcare diagnostics, and autonomous operations across multiple regulatory jurisdictions and ethical frameworks simultaneously. The combination of algorithmic influence, predictive capabilities, and automated decision-making authority makes thorough candidate verification essential for maintaining compliance, fairness, and public trust in AI-powered systems.