Data Analyst Apprentice

Fleetcor Europe
Meriden
1 year ago
Applications closed

Related Jobs

View all jobs

Data Analyst Apprenticeship

Data Analyst Apprenticeship

Data Analyst Apprenticeship...

Junior Data Analyst Apprenticeship

Lead Management, CX and Digital Communications Data Analyst Apprentice

Data Analyst Trainer

Your role We are currently looking for an apprentice data analyst with a passion for data and data visualisation to become part of our growing our data and technology team and help us build upon our current skills and capabilities. Reporting to one of our Engineering Managers, you will initially be a part time member of one of our squads working with Data Analytics engineers, Product Development team members and stakeholders. What you'll be doing Learn how to source, process and visualise Data to provide insights and inferences. Build reports and visualisations. Analyse data from our systems, products and services and establish how to create new data and insights from this data. Build data processing processes, data models and data marts. Spend time working with other data teams in our region. Build automated tests to ensure data quality throughout processes. Build relationships with our Data and Engineering community. Work with our engineering squads as part of your apprenticeship. Critical Thinking, Analysis and Problem Solving Strong communication skills You will be able to interpret processes and data, and ask relevant questions to help refine your understanding. You can demonstrate an ability to use your initiative, take responsibility, be organised and work independently where required. High degree of self-motivation and be able to learn using both own initiative and the provided training courses Willing and able to work remotely and feel confident using video chat About Corpay Corpay is a global technology organisation that is leading the future of commercial payments with a culture of innovation that drives us to constantly create new and better ways to pay. Our specialized payment solutions help businesses control, simplify, and secure payment for fuel, general payables, toll and lodging expenses. Millions of people in over 80 countries around the world use our solutions for their payments. All offers of employment made by Corpay (and its subsidiary companies) are subject to the successful completion of satisfactory pre-employment vetting by an independent supplier (Experian). This is in accordance with Corpay's Resourcing Policy and include employment referencing, identity, adverse financial, criminal and sanctions list checks. We do this to meet our legal and regulatory requirements. Corpay is dedicated to encouraging a supportive and inclusive culture among our employees. It is within our best interest to promote diversity and eliminate discrimination in the workplace. We seek to ensure that all employees and job applicants are given equal opportunities. Notice to Agency and Search Firm Representatives: Corpay will not accept unsolicited CV's from agencies and/or search firms for this job posting. Resumes submitted to any Corpay employee by a third party agency and/or search firm without a valid written & signed search agreement, will become the sole property of Corpay. No fee will be paid if a candidate is hired for this position as a result of an unsolicited agency or search firm referral. Thank you.

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.