Information & Data Analyst

SCOTTISH SOCIETY FOR THE PREVENTION OF CRUELTY TO ANIMALS
Dunfermline
1 month ago
Applications closed

Related Jobs

View all jobs

Information Security Data Analyst

Information Security Data Analyst

Information Security Data Analyst

Lead Information Security Data Analyst

Finance Data Analyst & Modeler (Graduate)

MI & Data Analyst

We are currently looking for an Information & Data Analyst. This role will be a hybrid role between Scottish SPCA Headquarters in Dunfermline with a flexible blend of home working.

If this sounds like a role you would be interested in, please read on for more information.

  • Hours – 35 hours per week, Monday to Friday
  • Salary – £27,499 per annum (FTE)
  • Contract Type – Permanent

About the Scottish SPCA

As Scotland’s animal welfare charity, we have been on-hand to protect animals and prevent cruelty since 1839 – that’s over 185 years of creating a better world for all animals. We’ve grown to become a national charity which celebrates the strength of the human-animal bond and enriches the lives of animals and people. We are Scotland’s animal champions.

What does an Information & Data Analyst do?

To take an active role in the scoping, development and implementation of management information reports and dashboards to support the strategic planning process at the Scottish SPCA. To source and supply accurate, timely and insightful management information and data for Senior Managers and other key stakeholders to inform evidence-based decisions and strategies regarding the Society’s organisational performance.

Overview of main duties and responsibilities

  1. To introduce data extraction, transformation and delivery methodologies and systems and work closely with other departments to collate key information which will drive and inform operational and strategic plans.
  2. Undertake robust analysis of key datasets relating to aspects of the Society’s performance and produce dashboards and other appropriate graphics that enable staff across the Society to make informed decisions.
  3. Analysis of large numerical datasets and presenting quantitative information extracted in clear, concise formats.
  4. To increase data literacy and promote the skills to support colleagues less familiar with the complexities of general data analytics and reporting.
  5. Develop and maintain trusted adviser relationships with colleagues and establish strong working ties with other staff with data coordination duties across the Society.
  6. Be responsible for supporting the continuous improvement and delivery of management information from our Animal Rescue and Rehoming Centres, Inspectorate and Helpline.
  7. Work proactively and collaboratively with other staff across the Society to influence and support continuous improvement in data quality and information management processes.
  8. To inform evidence-based decisions and strategies. To support the Head of Customer Experience in the delivery of business intelligence.
  9. To deliver a wide range of regular management information, providing informative advice and support to related data inquiries. Work in close liaison with colleagues across the Society to ensure that all management information reporting meets the agreed specifications and addresses end users’ requirements.
  10. To promote good data governance and take a lead role in delivering timely, accurate and relevant information necessary to support year-round management reporting.
  11. To develop the Society’s reporting and analytical tools, to actively contribute to the advance of data extraction, transformation and delivery methodologies.

What makes a good Information & Data Analyst?

  • Extensive experience of analysing large numerical datasets
  • High level of numeracy and statistical acumen
  • Experience of preparing briefing papers to share insights and develop understanding
  • Ability to prioritise stakeholder needs
  • Experience of data visualisation
  • Dashboard Creation
  • Automation of data
  • Providing and sharing insights
  • Experience using Tableau, Power BI or similar
  • Experience using marketing and ecommerce analytics and Google Analytics

We are fortunate that some of our roles attract a high level of interest therefore, we may have to close roles earlier than advertised. Early application submissions are highly recommended. This also means that we cannot provide individual feedback to unsuccessful candidates due to receiving high levels of applications.

The Scottish Society for Prevention of Cruelty to Animals is an Equal Opportunities Employer. We recognise that a diverse and inclusive workforce is essential to achieving our core mission.


#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.

How Many Data Science Tools Do You Need to Know to Get a Data Science Job?

If you’re trying to break into data science — or progress your career — it can feel like you are drowning in names: Python, R, TensorFlow, PyTorch, SQL, Spark, AWS, Scikit-learn, Jupyter, Tableau, Power BI…the list just keeps going. With every job advert listing a different combination of tools, many applicants fall into a trap: they try to learn everything. The result? Long tool lists that sound impressive — but little depth to back them up. Here’s the straight-talk version most hiring managers won’t explicitly tell you: 👉 You don’t need to know every data science tool to get hired. 👉 You need to know the right ones — deeply — and know how to use them to solve real problems. Tools matter, but only in service of outcomes. So how many data science tools do you actually need to know to get a job? For most job seekers, the answer is not “27” — it’s more like 8–12, thoughtfully chosen and well understood. This guide explains what employers really value, which tools are core, which are role-specific, and how to focus your toolbox so your CV and interviews shine.

What Hiring Managers Look for First in Data Science Job Applications (UK Guide)

If you’re applying for data science roles in the UK, it’s crucial to understand what hiring managers focus on before they dive into your full CV. In competitive markets, recruiters and hiring managers often make their first decisions in the first 10–20 seconds of scanning an application — and in data science, there are specific signals they look for first. Data science isn’t just about coding or statistics — it’s about producing insights, shipping models, collaborating with teams, and solving real business problems. This guide helps you understand exactly what hiring managers look for first in data science applications — and how to structure your CV, portfolio and cover letter so you leap to the top of the shortlist.

The Skills Gap in Data Science Jobs: What Universities Aren’t Teaching

Data science has become one of the most visible and sought-after careers in the UK technology market. From financial services and retail to healthcare, media, government and sport, organisations increasingly rely on data scientists to extract insight, guide decisions and build predictive models. Universities have responded quickly. Degrees in data science, analytics and artificial intelligence have expanded rapidly, and many computer science courses now include data-focused pathways. And yet, despite the volume of graduates entering the market, employers across the UK consistently report the same problem: Many data science candidates are not job-ready. Vacancies remain open. Hiring processes drag on. Candidates with impressive academic backgrounds fail interviews or struggle once hired. The issue is not intelligence or effort. It is a persistent skills gap between university education and real-world data science roles. This article explores that gap in depth: what universities teach well, what they often miss, why the gap exists, what employers actually want, and how jobseekers can bridge the divide to build successful careers in data science.