Director Data Analytics & AI

KPMG
Edinburgh
1 month ago
Applications closed

Related Jobs

View all jobs

Associate Director, Data Science and Innovation

Director of Healthcare Analytics

Director of Engineering - Advanced Analytics

Director of Artificial Intelligence - Manufacturing & Industrial

Lead Data Scientist[975963]

Director of Data Science & AI – Global Manufacturing Transformation

Job description

Director – AI

 

The Team
Many of our clients are undergoing rapid digital transformation, leveraging AI including Generative AI (GenAI) to drive operational efficiencies, enhance customer experiences, and mitigate reputational, financial and regulatory risks. Our highly specialised Data and AI team applies cutting-edge AI/GenAI techniques and industrial-scale cloud platforms to accelerate these journeys. Our projects involve processing vast and complex data sources, developing advanced AI models, and deploying scalable AI-driven solutions that create tangible business value.

 

Our UK-based AI team collaborates globally with KPMG's business, engineering and cloud specialists to design and implement state-of-the-art AI systems and products. We work across diverse industries, including Financial Services, Retail, Public Sector, Healthcare, Energy, and Utilities, enabling AI-powered decision-making and automation.

 

At KPMG, we believe in fostering an inclusive and diverse environment. Our strength lies in our people—their expertise, innovation, and unique perspectives. Join us to be part of an exciting AI-led transformation.


Roles & Responsibilities

 

Technical Leadership:

 

Lead and manage teams developing AI and GenAI solutions for enterprise-scale challenges, including:Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG)Autonomous AI Agents for workflow automationAI-powered decision intelligence systemsAI ethics and responsible AI implementation Deliver AI solutions across the full lifecycle, from PoCs and MVPs to production-grade deployments. Ensure AI model robustness, governance, security and regulatory compliance.

 

Business Development & GTM:

 

Develop market-facing AI offerings to drive revenue growth. Work closely with industry sector teams to tailor AI solutions for specific market needs. Shape AI/GenAI-enabled transformation programs and secure new business opportunities through innovative AI-driven solutions. Drive RFP responses and business development efforts, crafting compelling AI proposals that showcase technical excellence and commercial viability. Contribute to AI thought leadership by authoring white papers, participating in industry panels, and presenting at AI/GenAI conferences.

 

People:

Play a key role in the leadership team, driving the growth and development of our AI capability. Support team expansion through hiring, mentoring, and coaching colleagues to foster a high-performing, inclusive culture. Contribute to knowledge management, ensuring best practices, insights and innovations are effectively shared across the team. Oversee resource planning and process optimisation, enhancing operational efficiency and scalability.

 

The Person

Significant level of experience in AI, data science, data engineering and/or other technology related capabilities in one or multiple industries. BSc (MSc or PhD preferred) in Computer Science, Statistics, Engineering or similar technical field Strong background in AI engineering, software engineering, data engineering and data platforms, with a track record of overseeing full-stack development and delivering production-grade solutions. Proficient with programming languages used by data scientists and AI engineers such as Python, R, Scala. Proficient with modern development tools such as Git and Docker. Up-to-date knowledge and hands-on experience with AI/ML technologies, including a broad range of libraries and tools such as Azure AI/ML Studio, Azure OpenAI, GCP Vertex AI, LangChain, LangGraph, PyTorch, Scikit-learn. Excellent problem-solving skills and the ability to work collaboratively in a cross-functional team. Strong communication skills with the ability to communicate complex technical concepts clearly to non-technical stakeholders. Strong planning and organisation skills to work with a high-performance team, handle demanding clients and multitask effectively.

#LI-EH1

 

 

Get the latest insights and jobs direct. Sign up for our newsletter.

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

Industry Insights

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

Jobs

Portfolio Projects That Get You Hired for AI Jobs (With Real GitHub Examples)

In the fast-evolving world of artificial intelligence (AI), an impressive portfolio of projects can act as your passport to landing a sought-after role. Even if you’ve aced interviews in the past, employers in AI and machine learning (ML) are increasingly asking candidates to demonstrate hands-on experience through the projects they’ve built and shared online. This is because practical ability often speaks volumes about your suitability for a role—far more than any exam or certification alone could. In this article, we’ll explore how to build an outstanding AI portfolio that catches the eye of recruiters and hiring managers, including: Why an AI portfolio is crucial for job seekers. How to choose AI projects that align with your target roles. Specific project ideas and real GitHub examples to help you stand out. Best practices for showcasing your work, from writing clear READMEs to using Jupyter notebooks effectively. Tips on structuring your GitHub so that employers can instantly see your value. Moreover, we’ll discuss how you can use your portfolio to connect with top employers in AI, with a handy link to our CV-upload page on Artificial Intelligence Jobs for when you’re ready to apply. By the end, you’ll have a clear roadmap to building a portfolio that will help secure interviews—and the AI job—of your dreams.

Jobs Careers

AI Job Interview Warm‑Up: 30 Real Coding & System‑Design Questions

In today's competitive AI job market, nailing a technical interview can be the difference between landing your dream role and getting lost in the crowd. Whether you're looking to break into machine learning, deep learning, NLP (Natural Language Processing), or data science, your problem-solving skills and system design expertise are certain to be put to the test. AI‑related job interviews typically involve a range of coding challenges, algorithmic puzzles, and system design questions. You’ll often be asked to delve into the principles of machine learning pipelines, discuss how to optimise large-scale systems, and demonstrate your coding proficiency in languages like Python, C++, or Java. Adequate preparation not only boosts your confidence but also reduces the likelihood of fumbling through unfamiliar territory. If you’re actively seeking positions at major tech companies or innovative AI start-ups, then check out www.artificialintelligencejobs.co.uk for some of the latest vacancies in the UK. Meanwhile, this blog post will guide you through 30 real coding & system-design questions you’re likely to encounter during your AI job interview. This list is designed to help you practise, anticipate typical question patterns, and stay ahead of the competition. By reading through each question and thinking about the possible approaches, you’ll sharpen your problem-solving skills, time management, and critical thinking. Each question covers fundamental concepts that employers regularly test, ensuring you’re well-equipped for success. Let’s dive right in.

Jobs

Negotiating Your AI Job Offer: Equity, Bonuses & Perks Explained

Artificial intelligence (AI) has proven itself to be one of the most transformative forces in today’s business world. From smart chatbots in customer service to predictive analytics in finance, AI technologies are reshaping how organisations operate and innovate. As the demand for AI professionals grows, so does the complexity of compensation packages. If you’re a mid‑senior AI professional, you’ve likely seen job offers that include far more than just a base salary—think equity, bonuses, and a range of perks designed to entice you into joining or staying with a company. For many, the focus remains squarely on salary. While that’s understandable—after all, your monthly take‑home pay is what covers day-to-day expenses—limiting your negotiations to salary alone can leave considerable value on the table. From stock options in ambitious startups to sign‑on bonuses that ‘buy you out’ of your current contract, modern AI job offers often include elements that can significantly boost your long-term wealth and job satisfaction. This article aims to shed light on the full scope of AI compensation—specifically focusing on how equity, bonuses, and perks can enhance (or sometimes detract from) the overall value of your package. We’ll delve into how these elements work in practice, what to watch out for, and how to navigate the negotiation process effectively. Our goal is to provide mid‑senior AI professionals with the insights and tools to land a holistic compensation deal that accurately reflects their technical expertise, leadership potential, and strategic importance in this fast-moving field. Whether you’re eyeing a leadership role in machine learning at an established tech giant, or you’re considering a pioneering position at a disruptive AI startup, the knowledge in this guide will help you weigh the merits of base salary alongside the potential riches—and risks—of equity, bonuses, and other benefits. By the end, you’ll have a clearer sense of how to align your compensation with both your immediate lifestyle needs and long-term career aspirations.

🍪 We use cookies to enhance your browsing experience on our website. By continuing to use this site, you consent to the use of cookies as described in our Cookie Policy. You can review our Cookie Policy for more information.