Health and fitness is about behaviour change — and that makes it a fascinating data challenge.

You’ll work with rich customer, operational, and commercial data to:

• Understand how people join, engage, and stay active
• Optimise pricing, retention, and member experiences
• Build predictive models that genuinely influence business strategy

You’ll sit within a well-established Data & Insight team, working alongside Data Engineers, Analysts, and stakeholders across the organisation.

Data Science & Modelling

• Analyse customer and behavioural data across acquisition, retention, engagement, and pricing
• Build, validate, and optimise predictive models using robust statistical and ML techniques
• Carry out exploratory analysis to uncover patterns, test hypotheses, and quantify business impact
• Communicate insights clearly to both technical and non-technical audiences

ML Engineering & Production

• Deploy ML models into production within a modern cloud-based environment
• Build automated pipelines and CI/CD workflows to support training, testing, and deployment
• Monitor model performance, data drift, and reliability — keeping predictions accurate over time
• Work closely with Data Engineering to ensure high-quality, governed, model-ready data

Applied AI (Optional but encouraged)

• Explore how modern AI tools can enhance member experiences and internal processes
• Prototype AI-driven ideas through proofs of concept and lightweight demos
• Help shape responsible and practical AI adoption across the business

You’ll bring

• Strong Python (and/or PySpark) skills for analysis, modelling, and feature engineering
• Solid SQL experience
• A track record of delivering end-to-end predictive modelling projects
• Experience deploying and monitoring ML models in a cloud environment
• The ability to translate complex technical work into clear, commercial insight

• Exposure to MLOps or modern ML engineering practices
• Experience with AI prototyping or experimentation
• Cloud ecosystem experience (particularly Azure-based platforms)
• Interest in customer behaviour, subscriptions, or consumer products

• The chance to work on data products used by millions of members
• A role where your models move beyond notebooks into production
• Space to experiment, innovate, and explore emerging AI capabilities
• A collaborative, inclusive team culture that values impact over ego

Our client is a UK-based rapidly-growing technical consultancy delivering software and digital programmes across public sector organisations. Their model is to embed consultants into client teams, build strong relationships, and deliver outcomes with a practical, high-trust culture.

Key Responsibilities

• Designing and maintaining front-end automation for modern web apps (think Cypress/Playwright-style environments)
• Building or extending automation frameworks to suit different teams and projects
• Partnering with engineers, delivery leads, and clients to improve quality strategy and reduce release risk
• Contributing to best practice across QE (and helping others level up)
• Supporting testing in modern delivery setups (CI/CD pipelines, cloud-first environments, sometimes containerised services)

You’ll enjoy this if you:

• Care about quality outcomes, not just “tests passing”
• Can explain issues clearly to non-technical stakeholders
• Have strong automation experience for web/UI, and you’re comfortable getting hands-on
• Like variety: 6-month assignments, different clients, different problems
• Are SC-eligible (UK residency/travel constraints apply) and can travel to London/client sites when required

You’ll work in a consultancy environment where your work lands with real users — often on meaningful public-sector services — and where strong communicators thrive.

If you’re looking for a role where QA is respected, your voice matters, and you can build genuine credibility with clients, this is worth a conversation.

Because you want more than just writing test scripts.

Here, you’ll have real ownership over automation frameworks and testing strategy, the chance to work across varied, high-impact projects rather than one static product and will be joining a consultancy environment where progression is based on capability, not time served.

Our client is a growing technology consultancy that partners closely with organisations across the public and private sectors, embedding engineers into teams to solve real-world problems. They operate with a flat structure, value expertise over hierarchy, and invest heavily in their people. Consultants are encouraged to move between projects, broaden their skillsets, and shape their own career paths. Quality, collaboration, and pragmatism sit at the heart of everything they do.

You’ll be:

• Designing, building, and maintaining back-end automation frameworks

• Testing APIs and microservices using Java-based tools (e.g. RestAssured, contract testing)

• Integrating automated tests into CI/CD pipelines

• Working closely with developers, QA peers, and clients to improve quality end-to-end

• Helping establish best practice across automation and testing

This is a hands-on role – not a test management position.

You’ll likely have:

• Experience as an Automation Test Engineer / SDET

• Strong Java and API automation experience

• Exposure to building or extending automation frameworks

• A solid understanding of the SDLC and QA best practice

• Confidence working in client-facing, agile environments

If you enjoy autonomy, variety, and being trusted to deliver – you’ll feel at home here.

Our client is a fast-growing technical consultancy known for delivering bespoke software engineering on complex, high-impact programmes across the UK public sector. Their culture is flat, collaborative, and delivery-focused. Engineers are trusted to make decisions, work closely with stakeholders, and shape solutions from idea through to production. Projects are long-running, teams are stable, and engineering quality genuinely matters.

You’ll join an agile, client-embedded team delivering modern, scalable systems. Your work will include:

• Designing and building backend services using Java (12+) and Spring Boot

• Contributing to front-end development (ideally Angular, though React is welcome)

• Working across the full SDLC: requirements, build, test, deploy, support

• Applying TDD/BDD, clean code principles, and DevOps practices

• Collaborating directly with non-technical stakeholders to shape solutions

• Growing your cloud and DevOps capability (AWS/Azure, Docker, CI/CD)

Remote-first, with occasional on-site collaboration when it adds value. 🏡

You’ll likely be a mid-level full stack engineer who:

• Has strong commercial experience with Java and modern frameworks

• Is comfortable being client-facing and explaining technical decisions

• Enjoys working across backend and frontend, not just one layer

• Cares about code quality, learning, and continuous improvement

• Is eligible for UK security clearance (UK-based, no visa sponsorship)

If you want your engineering skills to be seen, trusted, and developed, this role is worth your attention. 👀

With over a decade of industry presence, this brand has expanded to more than 250 locations across the UK and proudly supports a community of over 500,000 members. They’ve built a reputation not just for their size and scale, but for a people-first culture and strong core values that are truly embedded across the business.

This is an exciting opportunity for a commercially minded Data Scientist to take ownership of end-to-end modelling and ML pipeline development within a fast-paced, consumer-focused organisation.

You’ll lead impactful work across the full lifecycle — from exploration and predictive modelling to deployment and automation — using modern cloud tooling to shape smarter pricing, retention, and customer insight. Alongside hands-on modelling, you’ll help strengthen MLOps practices and contribute to emerging AI initiatives, working closely with engineering and analytics teams to deliver scalable, high-value solutions.

Key attributes of the suitable Data Scientist include:

• Strong technical foundation in Python, SQL, and cloud-based ML workflows, with experience building and deploying end-to-end predictive models.
• Exposure to MLOps or ML engineering practices, including pipelines, CI/CD, model monitoring, and working with tools like Azure ML or Fabric.
• Commercially minded communicator who can translate data into clear, actionable insight and work collaboratively with technical and non-technical stakeholders.

1. MLOps & Azure Architecture

You’ll architect and build our entire cloud-native MLOps platform on Azure, including:

• High-throughput video processing infrastructure
• Robust data pipelines (Encord → Azure → Roboflow)
• Automated model training + versioning
• Deployment of high-performance inference services
• ETL pipelines to turn predictions into client-ready metrics

This is full system ownership — and you’ll be the one building it.

2. Computer Vision Strategy & Model Lifecycle

You will define how we track brand assets across sports video and social media content by:

• Designing the CV approach (models, data strategy, optimisation)
• Integrating Encord annotations with Roboflow training pipelines
• Deploying and optimising the model at scale
• Setting up monitoring to catch model drift before it becomes a problem

3. Human-in-the-Loop (HITL) Tooling

You’ll build the analyst verification interface that:

• Flags low-confidence detections
• Lets analysts quickly confirm/correct outputs
• Feeds improved data straight back into the training pipeline

This is the backbone of our continuous learning loop.

4. Knowledge Transfer

At the end of the project you’ll hand over:

• Documentation
• Architecture diagrams
• Runbooks
• Codebase walkthroughs

So our internal team can take full ownership.

🌟 Why This Role Is Special

• True ownership: You design it, you build it, you ship it.
• No legacy tech: Clean slate. You choose the right tools and architecture.
• Real-world impact: Your system will power visibility metrics used by global brands.
• Massive scope: MLOps, CV, cloud architecture, inference, ETL, HITL — all yours.
• Fast-moving domain: Sports + AI + video = one of the most exciting fields right now.

If you’re tired of being one engineer on a huge team and want to own the entire machine, this is your chance.

You don’t need every keyword — but you should have strong experience with:

• Building production MLOps systems on Azure
• Designing data pipelines and automated model lifecycles
• Deploying and optimising computer vision models (YOLO, Detectron, etc.)
• Working with annotation tools (Encord, Labelbox, Roboflow, etc.)
• Creating scalable inference systems for video/image workloads
• Building HITL or internal analyst tooling
• Shipping production systems in fast-paced environments

• 6-month contract (likely extension)
• Competitive day rate
• Hybrid initially then possible remote UK
• Start date: Jan 2026

Operating internationally, the company provides B2B research and insight services that help businesses make better decisions through data.

They specialise in market intelligence, competitor analysis, and sector-specific research across industries such as finance, private equity, Tech & FMCG.

This high-impact role combines strategic client advisory, advanced quantitative research, and team leadership across multiple sectors. If you’re driven by data, insight, and commercial outcomes – and want to shape strategies that matter – this is your chance to step into a pivotal leadership position with global reach.

Key attributes of the successful Research Director & Analytics include:

• Deep expertise in quantitative research methods – Conjoint, Max Diff, Segmentations, etc.
• Strong commercial mindset with a history of hitting revenue targets
• Proven leadership within a market research/analytics setting, with experience working across multiple sectors (ideally Financial Services or Tech)
• Experience of working with B2B Clients

This fast-growing business sits at the forefront of applied AI, working with major organisations to build and deploy intelligent systems that solve real operational challenges.

With a strong product roadmap and a collaborative culture, they offer the chance to work on high-impact projects in a fast-paced, forward-thinking engineering team.

This is a DevOps-centric, client-facing engineering role focused on getting AI systems—particularly agent-based solutions—successfully deployed into customer environments.

You’ll work across cloud, hybrid, and on-premise setups, navigating real-world constraints (networking, security, Kubernetes clusters, containerised workloads, etc.) and collaborating directly with clients to get solutions up and running.

You’ll work closely with senior engineering leadership to support deployments, contribute to agent-driven product builds, and ensure smooth delivery across varied technical landscapes.

Key attributes of the suitable DevOps Engineer (AI Deployment) include:

• Deployment & Delivery Experience – Hands-on experience deploying software or platforms into client environments (on-premise, hybrid or cloud).
• DevOps Foundations – Solid experience with Docker and Kubernetes (both essential), plus comfort working across different cloud providers and networking constraints.
• Interest in AI & Agents – Not a pure ML role—just curiosity or side projects involving AI agents, LLM tools, or automation frameworks.
• Client-Facing Mindset – Confidence working directly with customers, understanding their environments, and guiding them through deployment and solution delivery.
• Growth Mentality – 2+ years’ experience in DevOps, infrastructure, platform engineering or forward-deployed engineering roles.

This fast-growing business sits at the forefront of applied AI, working with major organisations to build and deploy intelligent systems that solve real operational challenges.

With a strong product roadmap and a collaborative culture, they offer the chance to work on high-impact projects in a fast-paced, forward-thinking engineering team.

This is a DevOps-leaning, client-facing engineering role focused on getting AI systems—particularly agent-based solutions—successfully deployed into customer environments.

You’ll work across cloud, hybrid, and on-premise setups, handling real-world constraints (networking, security, Kubernetes clusters, containerised workloads, etc.) and collaborating directly with clients to get solutions up and running.

You’ll work closely with senior engineering leadership to support deployments, contribute to agent-driven product builds, and ensure smooth delivery across varied technical landscapes.

Key attributes of the suitable AI Deployment Engineer:

• Deployment & Delivery Experience – Hands-on experience deploying software or platforms into client environments (on-premise, hybrid or cloud).
• DevOps Foundations – Solid experience with Docker and Kubernetes (both key), plus comfort navigating different cloud providers and networking constraints.
• Interest in AI & Agents – Not a pure ML role—just curiosity or side projects involving AI agents, LLM tools or automation frameworks.
• Client-Facing Mindset – Confidence working directly with customers, understanding their environments, and guiding them through deployment and solution delivery.
• Growth Mentality – 2+ years of experience in DevOps, infrastructure, platform engineering or forward-deployed engineering roles.

Because impact here isn’t theoretical – it’s lived. You’ll design experiments, run studies and translate insights into action that gets rolled out on the ground. This is work with purpose, backed by a team that genuinely values curiosity, rigour and innovation.

The role comes with a generous package too:

✨ £52–62k salary

✨ 40 days’ annual leave

✨ Private medical & dental

✨ 8% employer pension

✨ Learning and wellbeing allowance

✨ Cutting-edge AI tools to elevate your research workflow

✨ Hybrid working in London or Edinburgh (2–3 days in office)

Our client is a non-profit accelerator committed to improving early childhood outcomes. They combine data science, mixed-methods research and entrepreneurial thinking to design, test and scale evidence-based interventions.

They’re not a standard foundation. They roll up their sleeves:

➡️ identifying a challenge

➡️ researching it deeply

➡️ designing and trialling interventions

➡️ implementing solutions in real-world settings

Their mission is simple but bold: give every child the conditions to flourish.

No two weeks look the same, but you will:

• Lead mixed-methods research across quant, qual and secondary analysis.

• Design field experiments, online experiments and surveys.

• Work closely with data scientists to turn complex evidence into actionable programme insights.

• Shape organisational strategy and strengthen intervention design.

• Communicate findings through clear, compelling storytelling.

• Support and mentor junior researchers.

• Represent the organisation at events and conferences.

Your work will directly influence programmes that are tested and deployed across the UK.

You’ll thrive here if you:

• Bring 5+ years of applied research experience and strong mixed-methods confidence.

• Have experience designing trials, experiments or large-scale surveys.

• Can translate evidence into practical, impactful recommendations.

• Care deeply about early childhood, prevention, social policy or related fields.