Business Data Analyst - Data Acquisition and Insights

Financial Conduct Authority
Edinburgh
2 months ago
Applications closed

Related Jobs

View all jobs

Business Data Analyst

Business / Data Analyst

Business Data Analyst

Business Data Analyst

Business Data Analyst

Business Data Analyst Salesforce & Excel/VBA

Job Title: Business Data Analyst – Data Acquisition and Insights
Department: Data Strategy and Services
Division: Data, Technology and Innovation (DTI)



  • Salary: National (Edinburgh and Leeds) ranging from £43,100 to £53,700 and London £47,300 to £59,000 (salary offered will be based on skills and experience)


  • This role is graded as: Associate Level 8 – Regulatory


  • Your recruitment contact is Steve Christopher via . Applications must be submitted through our online portal. Applications sent via social media or email will not be accepted.



About the FCA and team

We regulate financial services firms in the UK, to keep financial markets fair, thriving and effective. By joining us, you’ll play a key part in protecting consumers, driving economic growth and shaping the future of UK finance services.


The Data, Technology and Innovation (DTI) division enables the FCA to be a digital-first, data-led smart regulator by delivering a secure, agile, and cost-effective technology and data ecosystem that drives better decisions, transparency, and operational efficiency. Sitting within DTI, the Regular Collections Team plays a key role in how the FCA create new (and improve existing) data reporting requirements for firms. They provide advice and support to regulatory colleagues and work with data and technology SMEs. The team own and are advocates for the FCA’s data collection framework, ensuring that the FCA gets the data it needs to meet its objectives whilst ensuring that the burden on firms is proportionate.


Role responsibilities

  • Collaborate across the FCA to improve regular data collections, strengthening regulatory decisions and delivering better outcomes for consumers


  • Analyse and prioritise data change requests, turning complex needs into clear use cases that enable timely, effective supervision


  • Engage with stakeholders to understand processes and needs, building shared understanding to co-create practical, proportionate data solutions


  • Apply data and business analysis techniques to investigate data and process issues, identifying root causes and improving data quality and reliability


  • Provide trusted advice and support to colleagues, resolving data acquisition challenges and enabling teams to deliver their work with clarity


  • Develop end-to-end knowledge of FCA data flows, connecting collection, governance and use to support a more joined-up organisation


  • Contribute to the FCA’s data-led transformation, influencing how data from c.35,000 firms is used to protect millions of UK consumers


  • Build a distinctive blend of data, analysis and stakeholder skills, broadening career opportunities and supporting future leadership roles



Skills required

Minimum:



  • Prior experience in business analysis and change projects, delivering outcomes and gathering data requirements for stakeholders


  • Experience in data-related roles demonstrating ability to interpret data, apply logical reasoning and use problem-solving skills to address complex issues


  • Proven experience in stakeholder engagement, building relationships, and clearly communicating technical concepts to non-technical audiences



Essential:



  • Demonstrable experience with core business tools and data analysis, including advanced Excel, SQL, Python, and data visualisation (Tableau preferred)




  • Analytical, numerical and data literate, being comfortable with quantitative concepts, data validation and understanding of data management activities that support data analysis


  • Accuracy and attention to detail, in analysis and communications with the ability to produce concise written and visual outputs


  • Ability to understand and document data requirements, including user and data needs, processes, and flows


  • Locate and access data using different channels and carry out analysis to identify issues, spot trends and arrive at a logical conclusion to support for data users and stakeholders


  • Experience working in agile environments, embracing flexibility and supporting iterative delivery throughout the project lifecycle


  • Collaborative approach, building trust and fostering inclusive teamwork to achieve shared goals


  • Strong organisational skills to manage multiple tasks effectively and keep stakeholders informed



Benefits

  • 25 days annual leave plus bank holidays


  • Hybrid model with up to 60% remote work


  • Non-contributory pension (8–12% depending on age) and life assurance at eight times your salary


  • Private healthcare with Bupa, income protection and 24/7 Employee Assistance


  • 35 hours of paid volunteering annually


  • A flexible benefits scheme designed around your lifestyle



For a full list of our benefits and our recruitment process as a whole visit our benefits page.


Our values and culture

Our colleagues are the key to our success as a regulator. We are committed to fostering a diverse and inclusive culture: one that’s free from discrimination and bias, celebrating difference and supports colleagues to deliver at their best. We believe that our differences and similarities enable us to be a better organisation – one that makes better decisions, drives innovation and delivers better regulation.


If you require any adjustments due to a disability or condition, your recruiter is here to help - reach out for tailored support.


We welcome diverse working styles and aim to find flexible solutions that suit both the role and individual needs, including options like part-time and job sharing where applicable.


Disability confident: our hiring approach

We’re proud to be a Disability Confident Employer and therefore, people or individuals with disabilities and long-term conditions who best meet the minimum criteria for a role will go through to the next stage of the recruitment process. In cases of high application volumes we may progress applicants whose experience most closely matches the role’s key requirements.


Useful information and timelines

Timeline:



  • Job advert close: 12 January 2026 at 11:59pm


  • CV Review/Shortlist: 14 January 2026


  • Case Study & Interview: w/c 19 January 2026


  • Your Recruiter will discuss the process in detail with you during screening for the role, therefore, please make them aware if you are going to be unavailable for any date during this time.



#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.