Data Scientist

Job Description

At Aberdeen, our ambition is to be the UK’s leading Wealth & Investments group.

Strengthening talent and culture is one of our strategic priorities. We strive to make Aberdeen a great place to work so that we can attract and retain the industry’s best talent.

Our people put our stakeholders at the heart of everything they do by helping us to make a positive difference to the lives of our clients, customers, colleagues, shareholders, and society.

We are focused on growing our direct and advised wealth platforms and repositioning our specialist asset management business to meet client demand. We are committed to providing excellent client service, supported by leading technology and talent.

Aberdeen comprises three businesses, interactive investor (ii), Investments, and Adviser, each of which focuses on meeting and adapting to our clients’ evolving needs:

interactive investor, the UK’s second largest direct-to-consumer investment platform, enables individuals in the UK to plan, save, and invest in the way that works for them.

Our Adviser business provides financial planning solutions and technology for UK financial advisers, enabling them to create value for their customers.

Our Investments business is a specialist asset manager that focuses on areas where we have both strength and scale to capitalise on the key themes shaping the market, through either public markets or alternative asset classes.
 

About the department
 

At Aberdeen Adviser, the Product Insights team helps the business understand how products perform, what customers experience, and where new opportunities lie. We bring together data engineering, analytics, and data science to produce insights that drive real decisions.
 

We work in cross-functional squads alongside product, engineering, and business colleagues.
 

Curiosity and experimentation are part of our culture, and we’re embracing automation and new tooling to deliver faster and smarter.
 

Most data science roles focus on building models. In Product Insights, we go further — helping shape the platform itself. That means equipping colleagues with the tools to do their best work and helping customers get more value from every interaction.
 

About the role
 

As a Data Scientist you’ll lead how we design, test, monitor, and govern models — from classical machine learning to agentic systems powered by large language models. You’ll report to the Head of Product Insights, with a broad remit to set direction and influence outcomes.
 

Key Responsibilities

Leading the design, development, validation, and governance of machine learning and agent-based models, including large language models and AI agents, ensuring safety, explainability, and alignment with business goals.

Developing and implementing inventive validation approaches and robust monitoring processes for models and agentic systems, including tracking behavior post-deployment for drift, bias, and fairness issues.

Designing and running experiments such as A/B tests, quasi-experiments, and causal inference studies to test hypotheses, measure business impact, and optimise decision-making.

Building scalable, reusable data pipelines for feature engineering and insight generation, automating workflows using Azure ML and Fabric, and applying best practices in MLOps for deployment and retraining.

Collaborating cross-functionally with product, engineering, and business teams to translate complex data science outputs into actionable insights understandable to both technical and non-technical stakeholders.

Mentoring junior colleagues and engaging senior leaders to shape data science strategy, promote a strong testing culture, support data governance, and drive the responsible adoption of emerging AI technologies in financial services.
 

About the candidate

Proficient in Python and/or R with strong engineering discipline and experience applying machine learning techniques including classical ML, NLP, and large language models (LLMs).

Solid grounding in statistics, causal inference, and advanced AI methods such as reinforcement learning and agentic systems, with a proven track record in model validation, monitoring, and governance.

Skilled in designing and running experiments including A/B testing, quasi-experiments, and causal inference for measuring impact and guiding data-driven decisions.

Familiarity with Azure ML, Fabric, medallion architecture, and MLOps best practices for model deployment, scaling, monitoring, and retraining.

Excellent communication skills capable of bridging technical and business teams, explaining complex data science outputs to diverse stakeholders.

Curious, open-minded, and engaged with emerging trends in data science and AI; able to mentor colleagues and influence senior stakeholders on data strategy and governance.
 

We are proud to be a Disability Confident Committed employer. If you have a disability and would like to apply to one of our UK roles under the Disability Confident Scheme, please notify us by completing the relevant section in our candidate questionnaire. One of our team will reach out to support you through your application process.
 

Our benefits
 

There's more to working life than coming home with a good salary. We have an environment where you can learn, get involved and be supported.
 

When you join us, your reward will be one of the best around. This includes 40 days’ annual leave, a 16% employer pension contribution, a discretionary performance-based bonus (where applicable), private healthcare and a range of flexible benefits – including gym discounts, season ticket loans and access to an employee discount portal. You can read more about our benefits 
 

Our business

Enabling our clients to be better investors drives everything we do. Our business is structured around three distinct areas – our vectors of growth – focused on our clients’ changing needs. You can find out more about what we do .
 

An inclusive way of working
 

Whatever way you like to work, if you have the talent and commitment to join our team, we’d like to hear from you.
 

At Aberdeen we’ve adopted a ‘blended working’ approach. This approach combines the benefits of face-to-face collaboration, coaching and connecting in our offices with the flexibility of working from home. It enables colleagues to find a balance that works for their roles, their teams, our clients and our business.
 

, where diverse perspectives drive our actions, is at the core of who we are and what we do.