Solution Architect (Advisory) - Insights & Data

83Zero
London
1 year ago
Applications closed

Related Jobs

View all jobs

Lead Data Scientist

Lead Data Scientist

Senior Practice Lead - Data Science_ UK

Machine Learning Engineer (Manager)

Head of DevOps and DataOps

Senior Lead Analyst - Data Science_ AI/ML & Gen AI

Solution Architect, Advisory, Insights & DataSalary: £110,000 - £120,000 - Bonus + Pension + Private HealthcareLocation: London / Birmingham / Manchester / Bristol / Glasgow - UK Wide Location - Hybrid working* To be successfully appointed to this role, you must be eligible for Security Check (SC) clearance .The Client:The Insights & Data Advisory practice is part of our client's global Insights & Data group. Their shared goal is to help the organisations they work with become truly 'data and insight driven', to fully exploit their data using the convergence of technologies, like Cloud and Artificial Intelligence, to deliver real business value.Your RoleSkilled Architects who bring a blend of consulting skills, with data and insights experience.Strong Management Consulting and board level Advisory experience with a proven track record helping clients shape their digital and data transformations strategies / roadmaps.You will be able to lead teams of talented colleagues across architecture, insights and data to transform the way companies and government operate.Our team is on a growth trajectory, and we are looking for someone to help to accelerate this growth.Your Skills and ExperienceProvide clearly articulated points of view on topics of focus, such as AI platforms, data engineering, security and privacy, DataOps, migration strategies etc.Be a lead for fresh engagements, forming excellent relationships with client teams and building bridges for delivery activitiesForge excellent links with related disciplines across the organisation, including AI engineering, cloud infrastructure, customer software development, consulting, systems engineering etc. And forge excellent links with partners and vendors across the industry to ensure that always provides a leading point of view.Experience:Advisory skillsets including consulting, influencing, communication, coaching and mentoring skillsStrong track record of architecting, designing and delivering complex large-scale data and/or analytics and AI centric solutionsExperience of architecting solutions deployed in cloud, on-prem and hybrid or multi-cloud environmentsTo apply please click the "Apply" button and follow the instructions.For a further discussion, please contact James Money on email:83zero is a boutique Tech & Data Recruitment Consultancy based within the UK. We provide high quality interim and permanent Tech & Data professionals.

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.

How Many AI Tools Do You Need to Know to Get an AI Job?

If you are job hunting in AI right now it can feel like you are drowning in tools. Every week there is a new framework, a new “must-learn” platform or a new productivity app that everyone on LinkedIn seems to be using. The result is predictable: job seekers panic-learn a long list of tools without actually getting better at delivering outcomes. Here is the truth most hiring managers will quietly agree with. They do not hire you because you know 27 tools. They hire you because you can solve a problem, communicate trade-offs, ship something reliable and improve it with feedback. Tools matter, but only in service of outcomes. So how many AI tools do you actually need to know? For most AI job seekers: fewer than you think. You need a tight core toolkit plus a role-specific layer. Everything else is optional. This guide breaks it down clearly, gives you a simple framework to choose what to learn and shows you how to present your toolset on your CV, portfolio and interviews.

What Hiring Managers Look for First in AI Job Applications (UK Guide)

Hiring managers do not start by reading your CV line-by-line. They scan for signals. In AI roles especially, they are looking for proof that you can ship, learn fast, communicate clearly & work safely with data and systems. The best applications make those signals obvious in the first 10–20 seconds. This guide breaks down what hiring managers typically look for first in AI applications in the UK market, how to present it on your CV, LinkedIn & portfolio, and the most common reasons strong candidates get overlooked. Use it as a checklist to tighten your application before you click apply.

The Skills Gap in AI Jobs: What Universities Aren’t Teaching

Artificial intelligence is no longer a future concept. It is already reshaping how businesses operate, how decisions are made, and how entire industries compete. From finance and healthcare to retail, manufacturing, defence, and climate science, AI is embedded in critical systems across the UK economy. Yet despite unprecedented demand for AI talent, employers continue to report severe recruitment challenges. Vacancies remain open for months. Salaries rise year on year. Candidates with impressive academic credentials often fail technical interviews. At the heart of this disconnect lies a growing and uncomfortable truth: Universities are not fully preparing graduates for real-world AI jobs. This article explores the AI skills gap in depth—what is missing from many university programmes, why the gap persists, what employers actually want, and how jobseekers can bridge the divide to build a successful career in artificial intelligence.