Senior data analyst

Made Tech Limited
London
1 month ago
Applications closed

Related Jobs

View all jobs

Senior Data Analyst

Senior Data Analyst

Senior Data Analyst

Senior Data Analyst (12 Month Contract)

Senior Data Analyst - HOTH, Permanent

Senior Data Analyst

As a Senior Data Analyst at Made Tech, you’ll play a pivotal role in helping public sector organisations become truly data-led. You’ll join our data team in its mission to get data knowledge and skills out of silos and embedded into delivery teams. You will provide advanced data modelling, predictive analytics, and data visualisation, allowing us to deliver more sophisticated and customised solutions to our clients.

Key responsibilities

  • Data analysis and reporting: Conducting in-depth data analysis, generating reports, and providing actionable insights for client projects.
  • Data and BI visualisation: Producing BI dashboards using industry-standard tools - Power BI, Tableau, Quicksight etc.
  • Client interaction: Collaborating with clients to understand their needs, translating these into analytical solutions, and presenting findings in a clear, actionable manner.
  • Mentoring and/or line managing: Junior analysts, leading data-focused projects, and setting best practices in data analysis.

Skills, knowledge and expertise

Technical skills:

  • Data Analysis & Insight Generation: Strong analytical skills, including statistical analysis, data mining, and qualitative research, with the ability to synthesise data into actionable insights.
  • Data Management & Governance: Knowledge of data storage, governance policies, and best practices, with experience in advocating for data quality and automating data management processes.
  • Data Modelling & Integration: Expertise in conceptual, logical, and physical data modelling, data cleansing, and integration using ETL tools to ensure accuracy and interoperability.
  • Data Visualisation: Proficiency in tools such as Tableau, Power BI, and Python visualisation libraries, with the ability to create clear, accessible, and engaging data presentations.
  • Quality Assurance & Validation: Experience in ensuring data accuracy through validation, cleansing, linkage, and peer review, while effectively communicating data limitations.
  • Statistical & Analytical Techniques: Knowledge of key statistical methods (e.g., regression, clustering, hypothesis testing) and ability to apply emerging analytical approaches to solve business challenges.

Business & Communication Skills:

  • Stakeholder Engagement: Strong communication and persuasion skills to engage technical and non-technical stakeholders, including sceptical colleagues.
  • Problem-Solving & Decision-Making: Logical and creative thinker, able to break down complex problems and develop innovative solutions.
  • Presentation & Storytelling: Skilled at translating complex data insights into clear, compelling narratives for senior management and diverse audiences.
  • Adaptability & Continuous Learning: A proactive mindset, eager to learn and improve processes, with the flexibility to adapt to evolving business needs.
  • Leadership: Proven track record of leading data projects and mentoring team members.

Support in applying

If you need this job description in another format, or other support in applying, please email .

We believe we can use tech to make public services better. We also believe this can happen best when our own team represents the society that actually uses the services we work on. We’re collectively continuing to grow a culture that is happy, healthy, safe and inspiring for people of all backgrounds and experiences, so we encourage people from underrepresented groups to apply for roles with us.

When you apply, we’ll put you in touch with a talent partner who can help with any needs or adjustments we may need to make to help with your application. This includes alternative formats for documents, the time allotted for interviews and any other needs. We also welcome any feedback on how we can improve the experience for future candidates.

Location:

Any UK Office Hub (Bristol / London / Manchester / Swansea)

Department:

Delivery & Practices > Data & AI Practice

Join us in our mission to use technology to improve society for everyone.


#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.

The Skills Gap in Machine Learning Jobs: What Universities Aren’t Teaching

Machine learning has moved from academic research into the core of modern business. From recommendation engines and fraud detection to medical imaging, autonomous systems and language models, machine learning now underpins many of the UK’s most critical technologies. Universities have responded quickly. Machine learning modules are now standard in computer science degrees, specialist MSc programmes have proliferated, and online courses promise to fast-track careers in the field. And yet, despite this growth in education, UK employers consistently report the same problem: Many candidates with machine learning qualifications are not job-ready. Roles remain open for months. Interview processes filter out large numbers of applicants. Graduates with strong theoretical knowledge struggle when faced with practical tasks. The issue is not intelligence or effort. It is a persistent skills gap between university-level machine learning education and real-world machine learning jobs. This article explores that gap in depth: what universities teach well, what they routinely miss, why the gap exists, what employers actually want, and how jobseekers can bridge the divide to build successful careers in machine learning.

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.