HR Data Analyst

Randstad Technologies Recruitment
Watford
1 year ago
Applications closed

Related Jobs

View all jobs

HR Data Analyst

HR Data Analyst

HR Systems & Data Analyst

Senior HR Data Analyst

Temporary HR & Reward Data Analyst...

Temporary HR & Reward Data Analyst

Here's a short and engaging job ad based on the description:HR Data Analyst | Hertfordshire | Hybrid | Competitive SalaryAre you a data-driven problem solver with expertise in Power BI, Business Objects, and Excel? We're looking for an HR Data Analyst to join our client's team and play a key role in delivering impactful HR analytics. What You'll Do:Build and maintain insightful HR reports and dashboardsEnsure data integrity and drive data-led decision-makingSupport automation initiatives to improve efficiencyCollaborate with HR and business stakeholders to provide key analytics What You'll Bring:Advanced Power BI, Business Objects, and Excel skillsStrong analytical mindset and experience handling complex dataAbility to work in a fast-paced, collaborative environmentNice to have: Power Automate, SQL, and automation experienceRandstad Technologies Ltd is a leading specialist recruitment business for the IT & Engineering industries. Please note that due to a high level of applications, we can only respond to applicants whose skills & qualifications are suitable for this position. No terminology in this advert is intended to discriminate against any of the protected characteristics that fall under the Equality Act 2010. For the purposes of the Conduct Regulations 2003, when advertising permanent vacancies we are acting as an Employment Agency, and when advertising temporary/contract vacancies we are acting as an Employment Business

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.

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.

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.