HR Systems & Data Analyst

Focus Group
Bellshill
1 year ago
Applications closed

Related Jobs

View all jobs

HR Systems Data Analyst, HISTORIC ENGLAND

Hybrid HR Systems Data Analyst (6-Month FTC)

Senior HR Data Analyst

Data Analyst (Software Systems Test)

Data Analyst Graduate

Human Resources Data Analyst

Job Title:           People Systems & Data Analyst

Department:     People & Culture

Salary:               £30,000 to £35,000

Location:           Any Focus Group office (Hybrid):

Glasgow / Manchester / Carlisle / Edinburgh / Birmingham / Exeter / Shoreham-by-Sea

Established in 2003, Focus Group is proud to be one of the UK’s fastest growing independent providers of essential business technology. The People & Culture function drives an employee centric, inclusive culture, delivering a high performing, entrepreneurial organisation that is a place where people love to work.

The People Systems and Data Analyst will own the production, analysis and monitoring of key HR metrics and insights. Ensuring the data is robust and accurate, identifying key areas of concerns and trends and recommendations for improvement. You will drive the HR data strategy, ensuring that HR data and Board reporting is of the highest possible standard and drives business performance.

You will also champion the HRIS and other HR systems ensuring that they seamlessly integrate with people processes enabling the people team to support the business effectively.  You work with and challenge the business to drive the people data agenda for the overall success of the business.

 

Principal Responsibilities/Duties

Data and reporting

  • Assist in ensuring the accuracy, reliability, and integrity of data used for HR reporting and analysis
  • Work with the Head of People Operations to ensure that data enables the business to manage its people effectively and measure the success of people initiatives
  • Assist in collecting data from various sources and performing cleaning and pre-processing
  • Conduct data validation and quality assurance to minimise errors and discrepancies
  • Use tools such as Microsoft Excel to extract, manipulate, and analyse data sets
  • Conduct exploratory data analysis to identify trends, patterns and anomalies in data
  • Provide analysis and interpretation of data relating to employee demographics, roles, responsibilities and organisational structures
  • Produce monthly People Board reports and other reporting required by the business
  • Responsible for collating the data and reporting on the Gender pay gap annually
  • Work closely with the People Operations and People Advisory teams through the acquisition process to ensure that the data from the newly acquired business is complete
  • Support the People Experience team with the analysis of the annual employee survey data to ensure we can effectively report on trends, patterns and improvements
  • Create detailed presentations and reports of HR data insights and present analytical results in a clear and concise manner
  • Work closely with the Business Partners and their areas of the business to create dashboards that share relevant people data and metrics to drive continuous improvement, people decisions and solutions.

HRIS

  • Manage the HRIS including data integrity and system developments, ensuring it is fit for purpose
  • Support and maintenance of the HR System. Providing direct user support to employees
  • Ability to write new reports and amending existing reports using report browsers exporting to excel to present the data
  • Support the Maintenance of the system including the creation and/or updating existing positions and employee data in system
  • Support the provision of reports to ensure they are received in a reasonable and timely manner
  • Support the testing of any changes, upgrades or enhancements to the system
  • Responsible for regularly undertaking data cleanses on the HRIS and other HR platforms to ensure that the data is up to date
  • Be a champion for change when new systems or policies are rolled out across Group

Compensation Processes

  • Provide support to the Compensation & Benefits Manager throughout the annual salary review and bonus process – managing the data throughout this process and analysing data to assist with calibration and budget management.

 

Requirements

Essential Skills

 

  • Advanced skills in Microsoft Excel
  • Understanding of statistical concepts and methodologies for analysing people metrics
  • Planning and attention to detail
  • Strong communication skills
  • Basic project management skills with the ability to prioritise tasks and manage deadlines
  • Ability to work to tight deadlines

 

Desirable Skills

  • Undergraduate qualification in Business, data analytics, administration or similar studies
  • Demonstrable experience as a HR administrator/coordinator
  • Experience with CIPHR, HIBOB or other HRIS

Benefits

At Focus Group you can be proud of what you do, how you do it and feel a true part of the team. We work hard to create an inclusive, collaborative and rewarding environment where you are inspired to achieve brilliant things and really make a difference to the future of our business.

We’re proud to have built an outstanding place to work where people thrive and are recognised for their achievements. We’re delighted to have been named one of the UK’s best 100 Companies to Work for 2021 and a British Private Equity & Venture Capital Association (BVCA) 2023 Vision Award Winner for London & South East for our commitment to culture and ESG.

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.