Data Scientist, Private Banking & Wealth Management (PBWM)
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What you'll do
- Drive and embed the design and implementation of data science tools and methods, which harness our data to drive market-leading purpose customer solutions.
- Act as a subject matter expert and articulate advanced data and analytics opportunities, bringing them to life through data visualisation.
- Understand the requirements and needs of our business stakeholders, form hypotheses, and identify suitable data and analytics solutions.
- Maintain and develop external curiosity around new and emerging trends within data science, keeping up to date with emerging trends and tooling.
- Proactively bring together statistical, mathematical, machine-learning and software engineering skills to consider multiple solutions, techniques, and algorithms.
- Implement ethically sound models end-to-end and apply software engineering and a product development lens to complex business problems.
- Work with and lead both direct reports and wider teams in an Agile way within multi-disciplinary data to achieve agreed project and Scrum outcomes.
- Use data translation skills to work closely with business stakeholders to define business questions, problems or opportunities.
- Select, build, train, and test complex machine models, considering model valuation, model risk, governance, and ethics throughout to implement and scale models.
What they're looking for
- Undergraduate or a master’s degree in a quantitative discipline, or evidence of equivalent practical experience.
- Evidence of project implementation and work experience gained in a data-analysis-related field as part of a multi-disciplinary team.
- Experience with statistical software, database languages, big data technologies, cloud environments and machine learning on large data sets.
- Experience of developing and managing the full model development life cycle of machine learning and AI products from concept to production.
- Demonstratable capability to deliver complex technical solutions aligned with business objectives and effectively communicate methodologies and outcomes in an accessible manner to non-technical stakeholders, exemplifying organisational change.
- Strong understanding of statistical models including, LASSO, Ridge, and Elastic Net, along with how they can be leveraged to drive pricing strategies of financial products, simulation techniques and core concepts of deep learning and Bayesian statistics.
- Expertise in developing Gen AI, Agentic AI tools for chat bots in addition to understanding workflows and evaluation methods to measure and monitor performance at scale.
- Managing ML, AI models in production with experience of CI/CD, DevOps, and model monitoring with strong risk management and governance awareness.
- Experience with cloud technology such as AWS and fluency with python and SQL.
- Ability to self-manage, take initiative and demonstrate a proactive approach to work.
- Effective verbal and written communication skills and the ability to adapt communication style to a specific audience.
Summarised by NextRaise from the employer’s description, which follows in full below.
Full description from employer
Join us as a Data Scientist, PBWM
- 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
- You’ll work from home some of the time, but you’ll also spend at least twice a week working from our Edinburgh or London office
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 gained in a data-analysis-related field as part of a multi-disciplinary team. We’ll also expect you to hold an undergraduate or a master’s degree in a quantitative discipline, or evidence of equivalent practical experience.
You’ll also need experience with statistical software, database languages, big data technologies, cloud environments and machine learning on large data sets, along with experience of developing and managing the full model development life cycle of machine learning and AI products from concept to production. We’ll also look to you to bring the ability to demonstrate leadership, self-direction and a willingness to both teach others and learn new techniques.
Additionally, you’ll need:
- Demonstratable capability to deliver complex technical solutions aligned with business objectives and effectively communicate methodologies and outcomes in an accessible manner to non-technical stakeholders, exemplifying organisational change
- Strong understanding of statistical models including, LASSO, Ridge, and Elastic Net, along with how they can be leveraged to drive pricing strategies of financial products, simulation techniques and core concepts of deep learning and Bayesian statistics are also required
- Expertise in developing Gen AI, Agentic AI tools for chat bots in addition to understanding workflows and evaluation methods to measure and monitor performance at scale
- Managing ML, AI models in production with experience of CI/CD, DevOps, and model monitoring with strong risk management and governance awareness
- Experience with cloud technology such as AWS and fluency with python and SQL
- Ability to self-manage, take initiative and demonstrate a proactive approach to work
- Effective verbal and written communication skills and the ability to adapt communication style to a specific audience
Hours
35Job Posting Closing Date:
27/09/2026Ways of Working:HybridCompany
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