Senior Data Analyst

Nucleus Financial
Edinburgh
2 months ago
Applications closed

Related Jobs

View all jobs

Senior Data Analyst

Senior Data Analyst

Senior Data Analyst

HR Senior Data Analyst

Senior Power BI Data Analyst

Senior Data Engineer

Senior Data Analyst | Technology

Role Specification: Senior Data Analyst


Team: Data Team


Reports to: Data Lead


Responsibilities

  • Lead and manage BI and data projects from inception to completion, including planning, scoping, prioritisation, and delivery, ensuring alignment with business objectives and timelines.
  • Collaborate with stakeholders to gather and refine requirements, prioritise incoming work for the team, and ensure that projects are well‑defined, achievable, and aligned with business needs.
  • Handle and respond to ad‑hoc data requests from various business units, providing timely and accurate insights to support decision‑making and operational needs.
  • Conduct in‑depth data analysis to identify trends, patterns, and actionable insights that inform business strategy and decisions.
  • Create and maintain BI reports, dashboards, and visualisations using tools such as Power BI to provide stakeholders with meaningful and accessible insights.
  • Ensure data quality, consistency, and accuracy across all BI outputs by developing and enforcing best practices, conducting data validation, and collaborating with developers where necessary.
  • Work closely with cross‑functional teams and stakeholders to understand their data needs, provide guidance on BI capabilities, and deliver solutions that add value.
  • Mentor analysts and developers, sharing best practices and fostering a culture of continuous improvement and development within the team.
  • Participate in Agile ceremonies such as sprint planning, stand‑ups, and retrospectives to help the team stay aligned, improve processes, and deliver effectively.

Key Skills

  • Advanced data analysis and SQL skills: strong experience in SQL for writing and optimising queries, performing complex analysis, and translating data into actionable insights.
  • BI tool expertise: proficiency in using BI tools such as Power BI to create meaningful reports and dashboards.
  • Project management proficiency: demonstrated experience in managing and delivering data and BI projects, including scoping, planning, prioritisation, and execution while balancing multiple tasks and stakeholders.
  • Strong communication and stakeholder management: excellent communication skills, with the ability to engage with both technical and non‑technical stakeholders and translate their needs into effective BI solutions.
  • Data quality and governance knowledge: understanding of data governance principles and practices, with experience ensuring data quality, consistency, and accuracy in BI outputs.
  • Mentorship and leadership: proven ability to mentor and guide team members, encouraging professional development and knowledge sharing.
  • Agile methodology understanding: experience working in an Agile environment, participating in Agile ceremonies, and contributing to iterative improvements in team processes.
  • Ad‑hoc analysis capabilities: ability to handle unplanned or ad‑hoc data requests efficiently and deliver quick, accurate insights to support business operations.

About Nucleus Group Services Limited

We are the Nucleus Group Services Limited and we help make retirement more rewarding. Here at Nucleus, people come first – whether it’s our colleagues, or the advisers and customers we support – we know that working in partnership and collaboration leads to the best outcomes.


Our ambition is to create a platform with a difference, putting the customer centre stage and starting from scratch. We’ve come a long way since then, but our mission remains just as focused. That’s why our culture, values and social responsibility stay at the top of our agenda – because we know they matter and have a big impact.


We want an environment where our people feel that they can make a real difference, know they’ll be rewarded for their efforts, and enjoy themselves at work.


Inclusion and Diversity

We care about inclusion. It’s not a tick‑box exercise; inclusion and diversity are embedded in our culture and everything we do. It’s a commercial imperative, a strategic priority and a foundation for a fair, balanced and transparent financial services sector.


We believe that more diversity means broader experience, a wider set of perspectives and a better collective ability to problem‑solve. It also means being more representative of customer groups, which supports product development and innovation.


Benefits

We offer a generous blend of benefits for the things that really matter to our people, including a non‑contributory pension, bonus, enhanced parental leave, paid time off for emergencies, health and wellbeing initiatives and flexible working options.


For more information about us or the role, please get in touch with our recruitment team.


#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.

How Many Machine Learning Tools Do You Need to Know to Get a Machine Learning Job?

Machine learning is one of the most exciting and rapidly growing areas of tech. But for job seekers it can also feel like a maze of tools, frameworks and platforms. One job advert wants TensorFlow and Keras. Another mentions PyTorch, scikit-learn and Spark. A third lists Mlflow, Docker, Kubernetes and more. With so many names out there, it’s easy to fall into the trap of thinking you must learn everything just to be competitive. Here’s the honest truth most machine learning hiring managers won’t say out loud: 👉 They don’t hire you because you know every tool. They hire you because you can solve real problems with the tools you know. Tools are important — no doubt — but context, judgement and outcomes matter far more. So how many machine learning tools do you actually need to know to get a job? For most job seekers, the real number is far smaller than you think — and more logically grouped. This guide breaks down exactly what employers expect, which tools are core, which are role-specific, and how to structure your learning for real career results.

What Hiring Managers Look for First in Machine Learning Job Applications (UK Guide)

Whether you’re applying for machine learning engineer, applied scientist, research scientist, ML Ops or data scientist roles, hiring managers scan applications quickly — often making decisions before they’ve read beyond the top third of your CV. In the competitive UK market, it’s not enough to list skills. You must send clear signals of relevance, delivery, impact, reasoning and readiness for production — and do it within the first few lines of your CV or portfolio. This guide walks you through exactly what hiring managers look for first in machine learning applications, how they evaluate CVs and portfolios, and what you can do to improve your chances of getting shortlisted at every stage — from your CV and LinkedIn profile to your cover letter and project portfolio.

MLOps Jobs in the UK: The Complete Career Guide for Machine Learning Professionals

Machine learning has moved from experimentation to production at scale. As a result, MLOps jobs have become some of the most in-demand and best-paid roles in the UK tech market. For job seekers with experience in machine learning, data science, software engineering or cloud infrastructure, MLOps represents a powerful career pivot or progression. This guide is designed to help you understand what MLOps roles involve, which skills employers are hiring for, how to transition into MLOps, salary expectations in the UK, and how to land your next role using specialist platforms like MachineLearningJobs.co.uk.