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

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.

With over a decade of market presence, this business has expanded to more than 150 locations across the UK, supporting a thriving community of over 500,000+ members. They’ve earned a reputation not only for their rapid growth but for fostering a genuinely people-first culture built on strong values and a commitment to continuous improvement.

This is a fantastic opportunity for a driven, hands-on performance marketer to accelerate their career within a high-growth, consumer-led organisation.

As Digital & Performance Marketing Executive, you’ll play a key role in driving member acquisition and brand growth through full-funnel digital and offline campaigns. You’ll plan, brief, execute, and optimise activity across PPC, paid social, YouTube, affiliates, programmatic, OOH, radio, VOD, CTV, and TV.

Working closely with internal teams and external agency partners to ensure campaigns are integrated, commercially effective, and constantly evolving in line with market best practice.

Key attributes of a successful Digital & Performance Marketing Executive include:

• 2–3 years’ experience in an acquisition-focused performance marketing role within a fast-paced, D2C or subscription-based environment.
• Ability to analyse and optimise campaigns to maximise ROI and support revenue growth.
• Comfortable working cross-functionally with Brand, CRM, Analytics, eCommerce, Design, and external media partners.
• Confident using GA4, Adobe Analytics, and visualisation tools such as Looker Studio or Power BI.
• Advanced Excel and PowerPoint skills, with the ability to turn performance insights into clear recommendations.

A growing consultancy at the forefront of behavioural science and human-centred design is expanding its Behavioural Intelligence capability — blending data science, behavioural analytics, experimentation and AI.

We’re looking for a curious, commercially minded Data Scientist who enjoys solving complex problems, finding behavioural patterns in data, and turning insights into simple, powerful stories.

You’ll work alongside behavioural scientists, researchers and consultants to deliver analytical projects for major clients across industries such as finance, retail, energy and utilities.

It’s the ideal next step for someone with solid technical foundations who wants to broaden into consulting, experimentation, behavioural analytics and insight-led storytelling.

Analyse Behavioural & Customer Data

• Work with varied datasets (implicit response data, transactions, qualitative transcripts).

• Build clustering, segmentation, predictive and ML models to explain and forecast behaviour.

• Support experimental design, hypothesis testing and behavioural measurement.

Create Impactful Insights

• Translate analytical findings into clear, behavioural and commercially grounded recommendations.

• Present insights to non-technical stakeholders and support consultants on client programmes.

Improve Tools & Workflows

• Contribute to reproducible code, documentation and internal data practices.

• Support automation, pipeline development and embedding analytics into client solutions.

Work Across Disciplines

• Partner with behavioural scientists, designers and strategists to combine data with human insight.

• Help develop the consultancy’s Behavioural Intelligence toolkit and AI-enabled ways of working.

• Around 2.5–5 years of experience in data science or applied analytics.

• Strong skills in Python and SQL (R a bonus).

• Experience with machine learning techniques (clustering, regression, NLP, ensemble methods).

• Good grounding in statistics (hypothesis testing, regression, experimental design basics).

• Ability to distil complex technical results into simple, engaging narratives.

• Curiosity about human behaviour and decision-making.

• Experience running end-to-end analytics projects.

Nice to have:

• Cloud experience (Azure, AWS or GCP).

• NLP / text analytics.

• Exposure to A/B testing.

• Understanding of behavioural science principles.

• Work at the intersection of data science and behavioural science — a rare and exciting blend.

• Solve meaningful, human-centred problems with real-world impact.

• Grow in a multidisciplinary environment that mixes behavioural research, consulting and AI.

• Join a culture that values curiosity, experimentation, rigour and continuous learning.

Benefits include: season ticket loan, cycle-to-work scheme, discounted gym membership, health screening & dental cover, EAP, free annual eye test, a well-stocked office kitchen and regular team socials.

If you want to grow into a more consultative, behavioural and experimental Data Scientist — this is the role.

Apply now.

With over a decade of industry presence, this brand has expanded to more than 150 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 outstanding opportunity for a commercially minded analytics professional to take ownership of the planning and insight function within a fast-paced, consumer-focused business.

As Analytics Lead, you’ll play a pivotal role in driving data-led decision-making across pricing, promotions, CRM, and digital performance. You’ll lead a small team, set analytical standards, and ensure insight directly influences strategy, marketing effectiveness, and overall revenue growth.

Key attributes of the suitable Analytics Lead include:

• Analytical Leadership: Proven experience in commercial, marketing, or digital analytics with strong SQL and statistical expertise (A/B testing, modelling, incrementality).
• Strategic Influence: Ability to connect complex data with commercial outcomes and provide clear, actionable recommendations to senior stakeholders.
• Team Development: Track record of leading, coaching, and developing analytics teams within a collaborative, high-performance environment.
• Data Visualisation & Communication: Advanced skills in Power BI (and ideally Looker Studio) with a flair for turning analysis into compelling stories and dashboards.

With over a decade of industry presence, this brand has expanded to more than 150 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 outstanding opportunity for a commercially minded analytics professional to take ownership of the planning and insight function within a fast-paced, consumer-focused business.

As Senior Analytics Manager, you’ll play a pivotal role in driving data-led decision-making across pricing, promotions, CRM, and digital performance. You’ll lead a small team, set analytical standards, and ensure insight directly influences strategy, marketing effectiveness, and overall revenue growth.

Key attributes of the suitable Senior Analytics Manager include:

• Analytical Leadership: Proven experience in commercial, marketing, or digital analytics with strong SQL and statistical expertise (A/B testing, modelling, incrementality).
• Strategic Influence: Ability to connect complex data with commercial outcomes and provide clear, actionable recommendations to senior stakeholders.
• Team Development: Track record of leading, coaching, and developing analytics teams within a collaborative, high-performance environment.
• Data Visualisation & Communication: Advanced skills in Power BI (and ideally Looker Studio) with a flair for turning analysis into compelling stories and dashboards.