Higher Data Analyst

Rural Payments Agency
Worcester
2 months ago
Applications closed

Related Jobs

View all jobs

HR Data Analyst

Overview

This is a brilliant time to join RPA. Our organisation is growing and we're at the heart of delivering the Government's agricultural transition and making a genuine difference to the health of our environment and rural economy. We continue to make year on year improvements in performance as we become a data and intelligence-led organisation, embedding our vision of customer excellence at every level and growing our reputation to make a difference every day. Our Data & Innovation Business Area is a multidisciplinary team including Geospatial Analysts, Data Engineers and Architects, Data Analysts and Intelligence Analysts. Together, we're in a unique position to use our specialist skills to work with the agricultural community to deliver big, impactful change, supporting high level environmental and animal welfare outcomes and the move towards net zero. This is a really exciting time to join our team as we grow and develop our ability to continuously analyse nationwide agricultural activity and provide agile, directed data and evidence-driven support to the farming community. We have clear values that we are embedding at every level in our organisation, improving engagement and innovating to be a more inclusive, supportive, and engaging employer. Our people own our values and bring them to life in everything we do. Recent new starters have talked glowingly about how supportive and caring their new colleagues are. We are proud of this culture; how open and approachable we are and our commitment to individual development, investing in the skills of our people and creating an environment in which everyone can flourish. Further details can be found at Rural Payments Agency - GOV.UK The roles being advertised are to cover a range of activities from data engineering, analysis and development all will sit within our Data and Analysis team, working closely with colleagues throughout the RPA.

Responsibilities

Provide data, analysis and insight to support the Agencies work, using the most appropriate tools and techniques.

Explore the large relational datasets available within our Data Warehouse, understanding how data interlinks and how meaningful analysis can be produced.

Undertake deep dives into subsets of data, utilising a range of analytical techniques to understand what the data is telling us and communicate it to customers and stakeholders.

Developing complex code to assure system rules and business logic is working correctly and develop tactical solutions where the system isn't functioning as needed, enabling the agency to achieve its customer service goals.

Work collaboratively with profiling and operational colleagues to develop intelligence on specific issues, analyse findings and draw appropriate inferences.

Explore the benefits of new technologies to bring efficiencies to the current service, and extend the scope of our analytical offering.

  • Enable efficient, effective and timely decision making, by providing high quality analysis, using the most appropriate data and methodology
  • Summarise and interpret information accurately, making use of different tools and data sources, to conduct analysis of key data sets using clear and simple terms
  • Utilise a range of data and intelligence to develop and maintain performance forecasting models, to help guide RPA's resource deployment decisions
  • Disability Confident
Disability Confident

A Disability Confident employer will generally offer an interview to any applicant that declares they have a disability and meets the minimum criteria for the job as defined by the employer. It is important to note that in certain recruitment situations such as high-volume, seasonal and high-peak times, the employer may wish to limit the overall numbers of interviews offered to both disabled people and non-disabled people. For more details please go to .


#J-18808-Ljbffr

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.

New Machine Learning Employers to Watch in 2026: UK and Global Companies Driving ML Innovation

Machine learning (ML) has transitioned from a specialised field into a core business capability. In 2026, organisations across healthcare, finance, robotics, autonomous systems, natural language processing, and analytics are expanding their machine learning teams to build scalable intelligent products and services. For professionals exploring opportunities on www.MachineLearningJobs.co.uk , understanding the companies that are scaling, winning investment, or securing high‑impact contracts is crucial. This article highlights the new and high‑growth machine learning employers to watch in 2026, focusing on UK innovators, international firms with significant UK presence, and global platforms investing in machine learning talent locally.

How Many Machine Learning Tools Do You Need to Know to Get a Machine Learning Job?

Machine learning is one of the most exciting and rapidly growing areas of tech. But for job seekers it can also feel like a maze of tools, frameworks and platforms. One job advert wants TensorFlow and Keras. Another mentions PyTorch, scikit-learn and Spark. A third lists Mlflow, Docker, Kubernetes and more. With so many names out there, it’s easy to fall into the trap of thinking you must learn everything just to be competitive. Here’s the honest truth most machine learning hiring managers won’t say out loud: 👉 They don’t hire you because you know every tool. They hire you because you can solve real problems with the tools you know. Tools are important — no doubt — but context, judgement and outcomes matter far more. So how many machine learning tools do you actually need to know to get a job? For most job seekers, the real number is far smaller than you think — and more logically grouped. This guide breaks down exactly what employers expect, which tools are core, which are role-specific, and how to structure your learning for real career results.

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.