Senior Data Analyst

Rathbone Brothers
Liverpool
1 month ago
Applications closed

Related Jobs

View all jobs

Senior Data Analyst

Senior Data Analyst

Senior Data Analyst

Senior Data Analyst

Senior Data Analyst

Senior Data Analyst

Senior Data Analyst

At Rathbones, we help people invest their money well, so they can live well. That means more than financial returns – it’s about helping people feel confident in their decisions and supported in their future. We don’t just manage money, we guide people through life’s big moments, helping them stay on track and focus on what matters most.


We’re proud to be one of the UK’s leading wealth managers, with over £109bn* in assets under management and 20+ offices across the UK and Channel Islands. We’re a FTSE 250 company with national reach and a local feel – and we’re growing. *As of June 2025


Employment details

Division: Data and Analytics
Location: Liverpool or Glasgow
Contract: Permanent
Working pattern: Hybrid


About the Role

In this role you will work closely with Business and Product teams to develop strategic data platforms. You will possess a strong mix of technical and business skills working towards strategic goals, whilst starting to develop management and leadership experience. You will be responsible for the definition of organisational data assets, and manipulating and linking different data sets across business units.


This is a newly created department focused on driving transformation by leveraging analytics, AI and data science. Working with the latest technology stack, you will be involved in high‑profile projects and initiatives. We currently offer a flexible, hybrid working approach.


What you’ll be responsible for

  • Work with the data team colleagues and business data offices to develop strategic initiatives to enable the organisation Strategy and deliver business outcomes
  • Analyse data using statistical techniques and communicate findings effectively
  • Examine complex data across business units to optimise the efficiency and quality of the data being collected, collaborate with the change delivery colleagues to improve systems and database designs
  • Embedding and supporting definition of best practice and ways of working across the group
  • Representing the Data office across the business and acting to establish culture and collaboration
  • Develop and maintain dashboards and reports using tools like Power BI or equivalent.
  • Create clear, compelling visualizations that communicate data-driven insights to non-technical stakeholders.
  • Automate regular reports and ad hoc analysis to support senior management, investment teams, and client advisors.
  • Act as a Data Partner with teams and across strategic programmes to understand business needs and translate them into data‑driven solutions.
  • Act as a trusted advisor on data matters, providing guidance on best practices for data analysis and reporting.
  • Actively support future proofing the business by applying AI, statistical and machine learning techniques to create predictive models that help anticipate client needs and enhance service offerings. Identify trends, patterns and opportunities within complex datasets related to wealth management and investment performance.

About you

If you meet some of these criteria and are excited about the role, we encourage you to apply:



  • The ability to work autonomously and as part of a team
  • Confident at managing relationships and communicating at all levels
  • Delivery oriented in an agile business environment
  • Analytical and problem‑solving skills – apply analytical techniques to present a solution
  • Data profiling, data cleansing, and data enrichment skills
  • Data visualisation – interpret requirements and present data in a clear and compelling way, using data visualisations
  • In this role you will need experience of the following as a minimum: Snowflake, SQL, Azure or AWS, Power BI and Python.

The wider technology stack is

  • Visualisation tools – Power BI
  • Data modelling tools – Python, R, Alteryx and Business Objects
  • Cloud service experience – AWS and/or Azure
  • Databases – SQL Server, Oracle, NoSQL
  • Data Integration tools – Mulesoft, Fivetran, SSIS
  • Cloud based Big Data frameworks such as data lake, Snowflake
  • Remote working, O365 Productivity stack

Our offer to you

We want everyone at Rathbones to fulfil their potential, in an environment where you are proud to work and feel like you belong.


We offer a comprehensive remuneration package, which we review regularly, and benefits include:



  • A company pension – 9% non‑contributory or 10% if you contribute 5%
  • Private medical insurance – Individual on joining, family after 1 year’s service
  • Life assurance – 8 x salary
  • Company share scheme
  • Discretionary bonus
  • Flexible holidays – purchase up to 5 additional days
  • Green Car Scheme
  • Family friendly policies – enhanced family leave for parents & carers
  • Study support – study days and funding for courses and qualifications
  • Season travel ticket loans
  • Other voluntary benefits you can choose to suit you

Social groups and communities

  • Sports & Social Committees, such as cricket, football, netball, running, yoga, quiz nights, charity bake sales and much more.
  • Inclusion Networks that help us drive change within the organisation such as Gender Balance, Multicultural, Abilities Count, Pride, Social Mobility, Generations, Take a moment to pause (Menopause) and Armed Forces.
  • The NextGen IM Network, which brings together a community of trainees from across the UK, who are all at the early stages of their careers and offers development opportunities, exposure across the business as well as peer support and connection.

Life at Rathbones

We aim to become an employer of choice for the wealth management sector, to achieve this we are working hard to build a diverse, equal and inclusive workplace that motivates, develops and embraces the strengths of all our colleagues. Being part of Rathbones means you will join a team of passionate professionals in a successful culture that cares for its people. At Rathbones, we provide meaningful work, opportunities and a voice to all.


We are committed to building a team that is made up of diverse skills, experiences and abilities and encourage applications from all backgrounds. We welcome individuals who share our values.


We’re a Level 1 Disability Confident employer under the UK Government scheme. This means we’ve signed up to a set of commitments around how we recruit, retain and develop people with disabilities. Find out more about the Government Scheme online.


If you feel there are any reasonable adjustments that would make the process easier for you and help you to perform at your best whether that is due to disability, neurodiversity or other protected characteristic, just let us know by emailing us at


Mission

We believe in playing the long game. That means building consistent results, earning trust and doing the right thing — for our clients, our colleagues and the communities we’re part of.


Our values shape how we work:
- We aim high
- We get it done
- We show we care
- We do the right thing


These aren’t just words on a wall. They guide how we treat each other, how we make decisions and how we build relationships that last.


We will close this advert once we have received enough applications for the next stage. Please submit your application as soon as possible to ensure you don’t miss out.


#J-18808-Ljbffr

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.

Machine Learning Jobs for Career Switchers in Their 30s, 40s & 50s (UK Reality Check)

Are you considering a career change into machine learning in your 30s, 40s or 50s? You’re not alone. In the UK, organisations across industries such as finance, healthcare, retail, government & technology are investing in machine learning to improve decisions, automate processes & unlock new insights. But with all the hype, it can be hard to tell which roles are real job opportunities and which are just buzzwords. This article gives you a practical, UK-focused reality check: which machine learning roles truly exist, what skills employers really hire for, how long retraining realistically takes, how to position your experience and whether age matters in your favour or not. Whether you come from analytics, engineering, operations, research, compliance or business strategy, there is a credible route into machine learning if you approach it strategically.

How to Write a Machine Learning Job Ad That Attracts the Right People

Machine learning now sits at the heart of many UK organisations, powering everything from recommendation engines and fraud detection to forecasting, automation and decision support. As adoption grows, so does demand for skilled machine learning professionals. Yet many employers struggle to attract the right candidates. Machine learning job adverts often generate high volumes of applications, but few applicants have the blend of modelling skill, engineering awareness and real-world experience the role actually requires. Meanwhile, strong machine learning engineers and scientists quietly avoid adverts that feel vague, inflated or confused. In most cases, the issue is not the talent market — it is the job advert itself. Machine learning professionals are analytical, technically rigorous and highly selective. A poorly written job ad signals unclear expectations and low ML maturity. A well-written one signals credibility, focus and a serious approach to applied machine learning. This guide explains how to write a machine learning job ad that attracts the right people, improves applicant quality and strengthens your employer brand.

Maths for Machine Learning Jobs: The Only Topics You Actually Need (& How to Learn Them)

Machine learning job adverts in the UK love vague phrases like “strong maths” or “solid fundamentals”. That can make the whole field feel gatekept especially if you are a career changer or a student who has not touched maths since A level. Here is the practical truth. For most roles on MachineLearningJobs.co.uk such as Machine Learning Engineer, Applied Scientist, Data Scientist, NLP Engineer, Computer Vision Engineer or MLOps Engineer with modelling responsibilities the maths you actually use is concentrated in four areas: Linear algebra essentials (vectors, matrices, projections, PCA intuition) Probability & statistics (uncertainty, metrics, sampling, base rates) Calculus essentials (derivatives, chain rule, gradients, backprop intuition) Basic optimisation (loss functions, gradient descent, regularisation, tuning) If you can do those four things well you can build models, debug training, evaluate properly, explain trade-offs & sound credible in interviews. This guide gives you a clear scope plus a six-week learning plan, portfolio projects & resources so you can learn with momentum rather than drowning in theory.