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

Apply Now

Data Scientist, Artificial Intelligence

NatWest Group
Edinburgh
1 week ago
Create job alert
Overview

Join us as a Data Scientist, Artificial Intelligence

  • You'll be identifying and working with large, complex data sets to solve difficult, non-routine analysis problems, applying advanced analytical methods as needed
  • We'll look to you to actively participate in the data community to identify and deliver opportunities to support the bank's strategic direction through better use of data
  • This is an opportunity to achieve excellent exposure in a challenging role and to make a real impact with your work
What you'll do

As a Data Scientist, you'll be helping to detect and reduce fraud using machine learning, scientific rigour and advanced statistical methods. You'll be supporting and collaborating with multidisciplinary teams of data engineers and analysts on a wide range of business problems including the prevention of financial crime, understanding customer interactions with the bank and the management of credit risk.

  • Developing and deepening your knowledge of data structures and model performance metrics, advocating for changes where needed for product development
  • Communicating effectively across our functions and franchises to make business recommendations, gaining business buy-in to solutions tailored to customers' needs
  • Conducting analysis that includes data gathering and requirements specification in collaboration with business stakeholders
  • Iteratively building and prototyping data analysis pipelines to provide insights that will ultimately lead to production deployment
  • Identifying new methods, tools, techniques and opportunities to deliver business value via cost reduction, income generation or improved customer experience through the application of data science
The skills you'll need

To succeed in this role, you'll need significant experience of developing and deploying supervised machine learning models, including classification algorithms, anomaly detection techniques, and network analysis methods. You'll be familiar with large language models (LLMs) and generative AI technologies.

You'll also need evidence of previous project implementation and work experience gained in a data analysis related field as part of a multidisciplinary team. Additionally, you'll hold a degree in a quantitative discipline or have evidence of equivalent practical experience.

You'll also demonstrate:

  • Sound knowledge of Python, SQL, version control (git) and familiarity with agile working practices
  • Experience with big data technologies (Spark, Hadoop) and cloud environments (preferably AWS)
  • Experience articulating and translating business questions and using statistical techniques to arrive at an answer using available data
  • The ability to demonstrate leadership, self-direction and a willingness to both teach others and learn new techniques
  • Excellent written and verbal communication skills and the ability to adapt the communication style to a specific audience
  • Extensive relevant work experience, with emphasis on statistical data analysis such as linear models, multivariate analysis, stochastic models and sampling methods
  • Experience with prompt engineering, fine-tuning, and integrating GenAI capabilities via APIs to deliver practical business solutions
Hours

35

Job Posting Closing Date: 08/10/2025

Ways of Working:Remote First


#J-18808-Ljbffr

Related Jobs

View all jobs

Lead/Senior Data Scientist

Junior Data Scientist

Lead Data Scientist | Health

Data Scientist Genomic Epidemiology - Pathogena

Junior Data Scientist (9624)

Junior Data Scientist (9624)

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.

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.

Why the UK Could Be the World’s Next Machine Learning Jobs Hub

Machine learning (ML) is becoming essential to industries across the globe—from finance and healthcare to retail, logistics, defence, and the public sector. Its ability to uncover patterns in data, make predictions, drive automation, and increase operational efficiency has made it one of the most in-demand skill sets in the technology world. In the UK, machine learning roles—from engineers to researchers, product managers to analysts—are increasingly central to innovation. Universities are expanding ML programmes, enterprises are scaling ML deployments, and startups are offering applied ML solutions. All signs point toward a surging need for professionals skilled in modelling, algorithms, data pipelines, and AI systems. This article explores why the United Kingdom is exceptionally well positioned to become a global machine learning jobs hub. It examines the current landscape, strengths, career paths, sector-specific demand, challenges, and what must happen for this vision to become reality.