Data Quality Analyst

Harnham
London
11 months ago
Applications closed

Related Jobs

View all jobs

Senior Data Analyst – Data Quality & Insights (Hybrid, Glasgow)

Associate Marine Water Quality Data Analyst

Hybrid Marine Water Quality Data Analyst

Data Analyst

Data Analyst – Transformation & Data Quality (Hybrid Edinburgh)

Data Analyst Rail

DATA QUALITY ANALYST

Take the next step in your career now, scroll down to read the full role description and make your application.£400-£425 PER DAY INSIDE IR35LONDON (3 DAYS IN THE OFFICE PER WEEK)6 MONTH CONTRACTTHE COMPANY:Join a data-driven company and contribute to their Data Management & Governance initiative, which aims to build and integrate standards and best practices that improve data quality.THE ROLE:As a Data Quality Analyst, you will predominately be responsible for supporting across a Data Management & Governance programme. This will include:Conducting root cause analysis of data quality issues and providing appropriate fixes.Assisting with the documentation of key data flows.Gathering requirements and liaising with stakeholders.Supporting ad-hoc data analysis and reporting requests from stakeholders.YOUR SKILLS AND EXPERIENCE:The successful Data Quality Analyst will be required to have the following experience:Proven experience as a Data Quality Analyst or in a similar role.Supported data quality/governance initiatives.Able to communicate effectively to a wide range of technical and non-technical stakeholders.Advanced skills in Excel, SQL, and Python.HOW TO APPLY:Please register your interest by sending your CV to Mojola Coker via the apply link on this page.

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.

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.

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.