Financial Data Analyst – Across multiple locations

First Choice Rec
Newtownards
4 days ago
Applications closed

Related Jobs

View all jobs

Financial Data Analyst – Across multiple locations

Financial Data Analyst – Across multiple locations

Financial Data Analyst

Senior Consultant - Data Analyst

Senior Data Analyst

Associate Data Analyst

Job Details

Job Type Full Time - Temporary
Location Downpatrick / Dundonald / Newtownards
Salary £15.66 per hour
Experience 4 years experience required
Closing Date 19-02-2026

Search

Posted 2 days ago

An opportunity has arisen for a Finance Analyst to support the monitoring, analysis and reporting of financial information in the South Eastern Trust.

This role is an ongoing temporary role, initially for 3 months, with the possibility of extension. The role is 37.5 hours per week and the working hours are 9am-5pm Monday – Friday with an hourly rate of £15.66 per hour.

The successful candidate can either be based in Newtownards, Dundonald or Downpatrick. The Finance Analyst will focus on monitoring, analysing, and reporting financial information to support the Trust’s Waiting List Initiatives, providing costing, benchmarking, and insight to help managers make informed decisions and improve efficiency across services.

What We Need From You

  • 4 years Experience in extracting, analysing and presenting data from complex datasets OR a relevant qualification in Finance, Accounting, Economics, Data Science or a related discipline
  • Strong analytical and numerical skills with the ability to present information clearly
  • Proficiency in Microsoft Office, particularly Excel
  • Excellent organisational and communication skills
  • Ability to work collaboratively as part of a team and use initiative when required

What We Will Offer You

  • Weekly pay
  • A minimum of 28 days paid holidays (pro rata)
  • Paid annual leave
  • Inclusion into our company pension scheme

The Next Steps

  • Contact Beth Wright on
  • Email your CV to

First Choice is an equal opportunities employer


#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.