Finance Data Science Manager

Jaguar Land Rover
Coventry
7 months ago
Applications closed

Related Jobs

View all jobs

Data Science Manager

Data Science Manager

Analytics Engineering Manager

Head of AI Technology - AI Innovation Team - Head of Data Science & Data Software Engineering (Hiring Immediately)

Head of AI Technology - AI Innovation Team - Head of Data Science & Data Software Engineering

Senior Data Scientist - Relay Network

Coventry

In a commercial role at JLR, you can reimagine the future of modern luxury. In teams focused on extraordinary customer experience, sustainability and forward-thinking. You’ll work alongside strategically-minded problem-solvers supporting the transformation of our iconic house of brands – Range Rover, Defender, Discovery, and Jaguar – and our heritage-rich JLR Classic range. Becoming a proud creator of the exceptional starts here.

WHAT TO EXPECT

Finance are on a journey to become a digital world class organisation and have created an Analytics and AI team, within Finance Transformation, to rapidly accelerate the development and deployment of Finance & Entity Data Products. The team consists of Data Engineers, Data Analytics and Enablement and Digital Product Owners. With strong data foundations being developed the plan is to extend the capability to include Data Science to leverage modern AI capabilities.


Key Accountabilities and Responsibilities

Establish and own the Data Science Strategy for Finance Deliver Finance Data Science Products  Establish process for review of solutions and scalability and reliability of data science products Liaison with DAIO teams on data science governance and technology requirements and operation Continually develop and maintain the standards for data science Manage and review data science deliverables

WHAT YOU’LL NEED

Proven previous experience establishing MLOps processes and technologies Understanding of the Data Science Model Development Process (CRISP-DM) Understanding of the IT Software Development Lifecycle (SDLC) Understanding of Google Cloud Platform (GCP) architecture patterns for MLOps Proven previous experience developing and deploying data science products Master expertise in Traditional AI - time series, optimisation, neural networks, regression, Graph AI

Creating Modern Luxury requires a modern approach to work. At JLR, hybrid working is a voluntary, non-contractual arrangement providing employees more choice and flexibility around how, when and where they work. Some roles require more on-site work, but details of this can be discussed with the hiring manager during the interview stage.

We work hard to nurture a culture that is inclusive and welcoming to all. We understand candidates may require reasonable adjustments during the recruitment process. Please discuss these with your recruiter so we can accommodate your needs. 

Applicants from all backgrounds are welcome. If you’re unsure that you meet the full criteria of a role – but you're interested in where it could take you – we still encourage you to apply. We believe in people's ability to grow and develop within their role – it’s what makes living the exceptional with soul possible.

JLR is committed to equal opportunity for all.

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.

AI Jobs at Newly Funded UK Start-ups: Q3 2025 Investment Tracker

Over the last decade, the United Kingdom has firmly established itself as one of Europe’s most significant technology hubs. Thanks to a vibrant ecosystem of venture capital, government-backed initiatives, and a wealth of academic talent, the UK has become especially fertile ground for artificial intelligence (AI) innovation. This growth is not just evident in established tech giants—new start-ups are emerging every quarter with fresh ideas, ground-breaking technologies, and a drive to solve real-world problems. In this Q3 2025 Investment Tracker, we take a comprehensive look at the latest AI start-ups in the UK that have successfully secured funding. Beyond celebrating these companies’ milestones, we’ll explore how these recent investments translate into exciting new job opportunities for AI professionals. Whether you’re an experienced machine learning engineer, a data scientist, or simply hoping to break into the AI sector, this roundup will give you insights into the most in-demand roles, the skills you need to stand out, and how you can capitalise on the current AI hiring boom.

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.

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.