Business Analyst - 6 Month FTC

Oulton, Suffolk
1 year ago
Applications closed

Related Jobs

View all jobs

Business Data Analyst

Business Data Analyst

Business Data Analyst

Business / Data Analyst

Business Data Analyst

Business Intelligence and Systems Analyst

Job Title: Business Analyst

Contract: 6 month FTC

Location: Lowestoft

Salary: £40,000 - £50,000 (DOE)

Our client is looking for a detail-oriented Business Analyst to join their dynamic finance team on a 6 month fixed term contract. This role involves preparing financial reports, analysing key metrics, and supporting forecasting and budgeting processes. The successful candidate will play a crucial role in providing insights to drive business performance and improve decision-making.

Key Responsibilities

Prepare weekly and monthly financial reports, analysing key metrics.
Conduct variance analysis to assess financial performance and identify key drivers.
Maintain accurate material and finished goods pricing through regular updates and analysis.
Assist in the month-end and quarter-end close process, including posting necessary accruals and journals.
Develop financial models to support forecasting and scenario planning.
Collaborate with finance and operational teams to enhance data governance and reporting accuracy.
Support continuous improvement initiatives, including automation and process optimisation.
Ensure compliance with internal controls and audit requirements.
Ideally, you will have a bachelor's degree in finance, accounting, or a related field. We welcome applications from qualified, part-qualified, or qualified-by-experience candidates. You should have a minimum of three years' experience in financial reporting and forecasting, along with strong analytical and problem-solving skills to interpret complex data. Proficiency in financial planning systems, SAP, and business intelligence tools is essential, as well as excellent communication and stakeholder management skills.

If you are a proactive finance professional looking for a new challenge, we'd love to hear from you. Please apply by sending your CV to (url removed)

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.