Data Scientist

NatWest Group; City of Edinburgh; Hybrid; GBP 55,000 - 75,000; Full time

Job summary

A major UK bank is seeking a Data Scientist in Edinburgh to drive the design and implementation of data science tools and methods. The candidate will work on advanced analytics opportunities and maintain relationships with business stakeholders. Key skills include NLP, cloud computing, and statistical analysis. This role operates in a hybrid work environment.

Qualifications

• Evidence of project implementation in data science or AI.
• Experience with statistical software and database languages.
• Proven leadership and self-direction skills.

Responsibilities

• Understand business stakeholder requirements and needs.
• Implement ethically sound models end-to-end.
• Lead multi-disciplinary teams in an Agile environment.

Skills

NLP-driven data science

Machine learning

Data visualization

Statistical analysis

Cloud computing

Education

Degree in a quantitative discipline

Tools

Tableau

Python

SQL

Job description

Join us as a Data Scientist

In this role, you'll drive and embed the design and implementation of data science tools and methods, which harness our data to drive market-leading purpose customer solutions. Day-to-day, you'll act as a subject matter expert and articulate advanced data and analytics opportunities, bringing them to life through data visualisation. If you're ready for a new challenge, and are interested in identifying opportunities to support external customers by using your data science expertise, this could be the role for you

What you'll do

We're looking for someone to understand the requirements and needs of our business stakeholders. You'll develop good relationships with them, form hypotheses, and identify suitable data and analytics solutions to meet their needs and to achieve our business strategy.

You'll be maintaining and developing external curiosity around new and emerging trends within data science, keeping up to date with emerging trends and tooling and sharing updates within and outside of the team.

You'll also be responsible for:

• Proactively bringing together statistical, mathematical, machine-learning and software engineering skills to consider multiple solutions, techniques, and algorithms
• Implementing ethically sound models end-to-end and applying software engineering and a product development lens to complex business problems
• Working with and leading both direct reports and wider teams in an Agile way within multi-disciplinary data to achieve agreed project and Scrum outcomes
• Using your data translation skills to work closely with business stakeholders to define business questions, problems or opportunities that can be supported through advanced analytics
• Selecting, building, training, and testing complex machine models, considering model valuation, model risk, governance, and ethics throughout to implement and scale models

The skills you'll need

To be successful in this role, you'll need evidence of project implementation and work experience in NLP-driven data science or AI fields, ideally as part of a multi-disciplinary team. A degree in a quantitative discipline (or equivalent practical experience) is expected.

You'll also need experience with statistical software, database languages, big data technologies, cloud environments, and machine learning on large datasets. Additionally you'll need to demonstrate leadership, self-direction, and a willingness to both teach and learn.

We'll also look for you to have:

• Experience deploying machine learning models into production, including LLMs and agentic systems with multi-turn dialogue management and autonomous decision-making
• The ability to translate business questions into data-driven solutions, using techniques like Retrieval-Augmented Generation (RAG), predictive modelling, and time series analysis
• Extensive experience in statistical data analysis, including linear models, multivariate analysis, and optimization techniques using calculus and linear algebra
• Proficiency with data visualization tools such as Tableau, or Power BI and Python libraries like, Matplotlib and Seaborn alongside SQL for data manipulation
• Strong foundation in cloud computing and Python, with familiarity in libraries like Pandas, NumPy, and scikit-learn
• Good understanding of LLM operations, including deployment on platforms like AWS Sage Maker, Google AI Platform, or IBM Watson

Hours: 35

Ways of Working: Hybrid

Job Posting Closing Date: 17/10/2025