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

Apply Now

Applied AI & Data Scientist

Slalom Consulting
City of London
5 days ago
Create job alert
Applied AI & Data Science Specialist | Senior Consultant

London | Manchester | Hybrid


About us – Slalom

Slalom is a purpose-led, global business and technology consulting company. From strategy to implementation, our approach is fiercely human. In six countries and 45 markets, we deeply understand our customers—and their customers—to deliver practical, end-to-end solutions that drive meaningful impact. Backed by close partnerships with over 400 leading technology providers, our 11,000+ strong team helps people and organisations dream bigger, move faster, and build better tomorrows for all. We are honoured to be recognised as a great place to work and named one of the UK\'s Fortune 100 Best Companies to Work For seven years running.


Since opening our doors in London in 2014, the Manchester office in 2019, and Dublin in 2023, we continue to grow. Our employees are at the heart of delivering impactful and meaningful work for our clients and helping them realise their vision.


Slalom\'s Data & AI Capability

At Slalom, we believe that through trusted client relationships we can create modern data and AI solutions that drive results. We offer opportunities across strategy, architecture, and hands-on delivery in the Engineering and AI space. Our AI capabilities span across machine learning, generative AI, and intelligent automation to unlock insights, streamline operations, and innovate faster. Whether you\'re building models, designing scalable AI platforms, or shaping ethical AI strategies, you\'ll be part of a team making a real impact. Slalom works with a range of data cloud partnerships including: AWS, Azure, Snowflake and Databricks.


The Role

We\'re seeking an Applied AI & Data Science Specialist to join a multi-disciplinary AI team that combines expertise in machine learning, generative and agentic AI, optimisation, and design to build intelligent, responsible, and scalable solutions.


No one can know it all – AI is vast and fast-moving. We value curiosity, collaboration, and breadth of understanding across domains more than mastery of any single discipline.


What you will do

  • Apply AI and data science methods from predictive modelling to Generative and Agentic AI to solve real business problems.
  • Use mathematical optimisation and analytical modelling to improve operations and resource efficiency.
  • Design and prototype AI workflows, copilots, and intelligent agents that enhance decision-making and productivity.
  • Contribute to AI system design and productionisation, ensuring scalability, performance, and ethical integrity.
  • Collaborate within a diverse team of strategists, data scientists, engineers, and designers to translate ideas into impact.
  • Stay current on AI trends, tools, and governance, fostering responsible and transparent adoption.

What you will bring

  • Degree in Data Science, Artificial Intelligence, Applied Mathematics, or related field.
  • Experience applying AI and analytics to real-world challenges.
  • Familiarity with Generative AI tools and frameworks (e.g., OpenAI, LangChain, Azure AI).
  • Working knowledge of optimisation, modelling, and AI lifecycle practices.
  • Strong communication skills with the ability to bridge technical and business perspectives.

What We Offer

  • Opportunity to work at the intersection of data, design, and applied AI innovation.
  • Access to cutting-edge technologies and cross-functional expertise in AI, analytics, and optimisation.
  • A collaborative and growth-oriented culture that values experimentation and impact.

We have a question for you – and it\'s something we\'re passionate about. Can you imagine a world in which you can truly love your life and your work? We have good news: creating that world and making this vision a reality is what we get out of bed for; it\'s our north star.


But what do we really mean when we talk about loving your life and your work? Let\'s take a look at the ways in which we help our team members to achieve this – and the \'how\'.


Deep connections, better outcome

We have deep relationships with over 400 leading technology partners and our approach is outcome-based. Our people are passionate about solving our clients\' problems using the tech that\'s best for them. We work side-by-side with client teams to enable success long after we\'ve gone, driving momentum that outlasts us.


Flexibility

Life is busy and we recognise that. We support our people in prioritising what matters while also working on high-impact projects they\'ll love.


People-first

Great solutions start with great people. We empower our team to be their authentic selves, guided by kindness, empathy, and equity. Inclusion, diversity and equity are central to our culture, and we strive to create better experiences for our people and clients.


Rewards

Compensation and benefits are competitive. We have a dedicated team ensuring packages are fair, competitive, and rewarding.


Take a look at the role below and if something sparks your interest, apply!


Want to learn more?


Get in touch!


If you require any assistance with regards to reasonable adjustments during the recruitment process, please do not hesitate to contact us – we will always be happy to help.


#LI-hybrid


#LI-SM


#J-18808-Ljbffr

Related Jobs

View all jobs

Applied AI & Data Scientist

Applied AI & Data Scientist

Applied AI, Senior/Staff Forward Deployed Machine Learning Engineer - EMEA

AI Engineer - Data/MLOps

AI Data Scientist

Data Science Manager (Applied AI)

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.

Machine Learning Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK machine learning hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise shipped ML/LLM features, robust evaluation, observability, safety/governance, cost control and measurable business impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for ML engineers, applied scientists, LLM application engineers, ML platform/MLOps engineers and AI product managers. Who this is for: ML engineers, applied ML/LLM engineers, LLM/retrieval engineers, ML platform/MLOps/SRE, data scientists transitioning to production ML, AI product managers & tech‑lead candidates targeting roles in the UK.

Why Machine Learning Careers in the UK Are Becoming More Multidisciplinary

Machine learning (ML) has moved from research labs into mainstream UK businesses. From healthcare diagnostics to fraud detection, autonomous vehicles to recommendation engines, ML underpins critical services and consumer experiences. But the skillset required of today’s machine learning professionals is no longer purely technical. Employers increasingly seek multidisciplinary expertise: not only coding, algorithms & statistics, but also knowledge of law, ethics, psychology, linguistics & design. This article explores why UK machine learning careers are becoming more multidisciplinary, how these fields intersect with ML roles, and what both job-seekers & employers need to understand to succeed in a rapidly changing landscape.

Machine Learning Team Structures Explained: Who Does What in a Modern Machine Learning Department

Machine learning is now central to many advanced data-driven products and services across the UK. Whether you work in finance, healthcare, retail, autonomous vehicles, recommendation systems, robotics, or consumer applications, there’s a need for dedicated machine learning teams that can deliver models into production, maintain them, keep them secure, efficient, fair, and aligned with business objectives. If you’re hiring for or applying to ML roles via MachineLearningJobs.co.uk, this article will help you understand what roles are typically present in a mature machine learning department, how they collaborate through project lifecycles, what skills and qualifications UK employers look for, what the career paths and salaries are, current trends and challenges, and how to build an effective ML team.