Graduate Data Analyst

Bristol
8 months ago
Applications closed

Related Jobs

View all jobs

Graduate Data Analyst - Python

Graduate Data Analyst - Power BI

Graduate Data Analyst: Client Solutions & Growth

Graduate Data Science & Analytics Programme

Graduate Data Scientist

Graduate Clinical Data Analyst

Provelio are currently looking for a Graduate Data Analyst to join their growing team in the South West and/or London to help deliver a diverse portfolio of data development projects.

The analyst will assist in the following activities:

  • Produce any project initiation documentation, project proposals and appointment terms.

  • Agree and action any technical and quality strategies for gathering the required data or information flows.

  • Help clients make evidence-based decisions to reduce their costs and drive productivity.

  • Be responsible for project administration.

  • Develop and maintain complex data models in SQL Server and PowerBI.

  • Translate raw inputs into meaningful management information.

  • Able to provide clear and succinct briefs to clients and other stakeholders on project requirements/findings.

  • Identify best practice approaches for data modelling to ensure continual improvement.

  • Clearly document key assumptions and processes to enable client and other stakeholders to replicate and understand your data models.

  • Able to direct and motivate others in the project team.

  • Manage project risks and issues including the development of contingency/mitigation plans.

    The successful candidate will demonstrate the following capabilities:

  • Able to demonstrate a strong understanding of Microsoft Excel for data transformation, modelling and data analysis.

  • Able to manipulate and restructure data using SQL.

  • Experience in SQL Server or equivalent database platforms.

  • Proficient in PowerBI DAX Code and using PowerBI to demonstrate complex issues to laymen users.

  • Maintains a strong attention to detail and is able to analyse information critically.

  • Maintain self-discipline and focus on the task at hand with minimal supervision.

  • Ability to scrutinise your own work before presenting it to senior management or clients.

  • Able to learn and adapt quickly under strict time constraints.

  • Able to interpret data and put findings into context.

  • Proficient in other Microsoft Office programmes

    Benefits

    Provelio take pride in investing in their employees and rewarding success. Our benefits and reward package for all employees includes...

  • Company Bonus Schemes

  • Training and Chartership Sponsorship

  • Payment of Professional Membership Fees

  • Hybrid Working

  • Enhanced Holiday Entitlement (28 days plus bank holidays)

  • Workplace Pension (above statutory minimum)

  • Additional Annual Leave for Reserves

  • Access to 24/7 Employee Assistance Programme (inc. GP services)

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 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.

Neurodiversity in Machine Learning Careers: Turning Different Thinking into a Superpower

Machine learning is about more than just models & metrics. It’s about spotting patterns others miss, asking better questions, challenging assumptions & building systems that work reliably in the real world. That makes it a natural home for many neurodivergent people. If you live with ADHD, autism or dyslexia, you may have been told your brain is “too distracted”, “too literal” or “too disorganised” for a technical career. In reality, many of the traits that can make school or traditional offices hard are exactly the traits that make for excellent ML engineers, applied scientists & MLOps specialists. This guide is written for neurodivergent ML job seekers in the UK. We’ll explore: What neurodiversity means in a machine learning context How ADHD, autism & dyslexia strengths map to ML roles Practical workplace adjustments you can ask for under UK law How to talk about neurodivergence in applications & interviews By the end, you’ll have a clearer sense of where you might thrive in ML – & how to turn “different thinking” into a genuine career advantage.