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

Apply Now

Lead Data Scientist

Nottingham
5 days ago
Applications closed

Related Jobs

View all jobs

Lead Data Scientist

Lead Data Scientist - Remote

Senior / Lead Data Scientist - AI Agents - Outside IR35

Lead R Data Scientist - Sustainability

Lead Full-stack Data Scientist

Staff Data Science

Lead Data Scientist

  • Based in Nottingham

  • 4 days a week onsite

  • Pay £50k-£60k depending on experience

    Our client is a fast-growing financial services organisation seeking a Lead Data Scientist to join their data and analytics team. This is a hands-on role focused on developing predictive models, deploying autonomous decisioning frameworks, and driving innovation across the customer lifecycle.

    The successful candidate will work closely with cross-functional teams to deliver data-driven solutions in fraud prevention, marketing, credit risk, and customer management. This is an exciting opportunity for a commercially experienced data scientist to take ownership of key initiatives and shape the future of data science within a forward-thinking environment.

    Role and Responsibilities:

  • Develop and deploy predictive models to improve customer outcomes across multiple business areas.

  • Lead model implementation and policy setting to support autonomous decision-making.

  • Design and execute test-and-learn strategies to inform business decisions.

  • Deliver actionable insights through structured analysis and clear communication.

  • Identify opportunities for process improvement and innovation using data.

    Key Skills and Experience:

  • 5+ years of experience delivering end-to-end data science solutions in a commercial setting.

  • Strong technical expertise in machine learning, predictive modelling, and AI.

  • Proficient in Python, R, SQL, and familiar with Power BI or similar visualisation tools.

  • Experience applying Gen AI tools or techniques is highly desirable.

  • Solid understanding of stakeholder engagement and business communication.

  • Educated to degree level (2:1 or above) in a numerical discipline.

  • Ability to work independently and collaboratively within a small team (5 people).

    Don't miss this opportunity to take a leading role in shaping data science strategy within a dynamic financial services organisation. Apply now with your most up-to-date CV!

    Please be aware this advert will remain open until the vacancy has been filled. Interviews will take place throughout this period, therefore we encourage you to apply early to avoid disappointment.

    Tate is acting as an Employment Business in relation to this vacancy.

    Tate is committed to promoting equal opportunities. To ensure that every candidate has the best experience with us, we encourage you to let us know if there are any adjustments we can make during the application or interview process. Your comfort and accessibility are our priority, and we are here to support you every step of the way. Additionally, we value and respect your individuality, and we invite you to share your preferred pronouns in your application

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.

Jobs

Top 10 Skills in Machine Learning According to LinkedIn & Indeed Job Postings

Machine learning (ML) is at the forefront of innovation, powering systems in finance, healthcare, retail, logistics, and beyond in the UK. As organisations leverage ML for predictive analytics, automation, and intelligent systems, demand for skilled practitioners continues to grow. So, which skills are most in demand? Drawing on insights from LinkedIn and Indeed, this article outlines the Top 10 machine learning skills UK employers are looking for in 2025. You'll learn how to demonstrate these capabilities through your CV, interviews, and real-world projects.

Careers

The Future of Machine Learning Jobs: Careers That Don’t Exist Yet

Machine learning (ML) has become one of the most powerful forces reshaping the modern world. From voice assistants and recommendation engines to fraud detection and medical imaging, it underpins countless applications. ML is no longer confined to research labs—it powers business models, public services, and consumer technologies across the globe. In the UK, demand for machine learning professionals has risen dramatically. Organisations in finance, retail, healthcare, and defence are embedding ML into their operations. Start-ups in Cambridge, London, and Edinburgh are pioneering innovations, while government-backed initiatives aim to position the UK as a global AI leader. Salaries for ML engineers and researchers are among the highest in the tech sector. Yet despite its current importance, machine learning is only at the beginning of its journey. Advances in generative AI, quantum computing, robotics, and ethical governance will reshape the profession. Many of the most vital machine learning jobs of the next two decades don’t exist today. This article explores why new careers will emerge, the roles likely to appear, how today’s roles will evolve, why the UK is well positioned, and how professionals can prepare now.

Jobs

Seasonal Hiring Peaks for Machine Learning Jobs: The Best Months to Apply & Why

The UK's machine learning sector has evolved into one of Europe's most intellectually stimulating and financially rewarding technology markets, with roles spanning from junior ML engineers to principal machine learning scientists and heads of artificial intelligence research. With machine learning positions commanding salaries from £32,000 for graduate ML engineers to £160,000+ for senior principal scientists, understanding when organisations actively recruit can dramatically accelerate your career progression in this pioneering and rapidly evolving field. Unlike traditional software engineering roles, machine learning hiring follows distinct patterns influenced by AI research cycles, model development timelines, and algorithmic innovation schedules. The sector's unique combination of mathematical rigour, computational complexity, and real-world application requirements creates predictable hiring windows that strategic professionals can leverage to advance their careers in developing tomorrow's intelligent systems. This comprehensive guide explores the optimal timing for machine learning job applications in the UK, examining how enterprise AI strategies, academic research cycles, and deep learning initiatives influence recruitment patterns, and why strategic timing can determine whether you join a groundbreaking AI research team or miss the opportunity to develop the next generation of machine learning algorithms.

🍪 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.