Business Intelligence Analyst

Leeds
1 year ago
Applications closed

Related Jobs

View all jobs

Business Intelligence Analyst

Business Intelligence Analyst

Business Intelligence Analyst

Business Intelligence Analyst (Forecasting/Planning Analytics)

Business Intelligence Analyst

Business Intelligence Analyst

BI Analyst

Based: Leeds (20%)

Duration: 6 months

Band: 7 £30.41 - £35.81 per hour (Band 7)

IR35: In scope

This will be a key post in the development of the Business Intelligence function, providing support to current data collection, modelling and reporting processes and being integral to their development, and also the development of new processes and outputs to ensure the Business Intelligence function supports the aims of client.

Advanced knowledge of Microsoft Excel
Create and maintain business intelligence (BI) reports and dashboards using available tools, in accordance with requirements gathered from both technical and non-technical end users.
Analyse and continually evaluate data quality and integrity to produce reports and implement action plans to ensure on-going process improvements.
Monitor established reporting to ensure data quality and integrity is maintained
Deal with non-routine enquiries providing advice as necessary
Provide support in responding to information requests and parliamentary questions
Ability to manipulate, model and analyse data using Excel, SQL, QlikView, Qlik Sense
Experience developing reports using data visualisation tools such as QlikView, Qlik Sense, Tableau or Power BI
Experience in processes related to data collection, modelling and processing data to maintain a trusted data source
Experience creating ad hoc SQL queries of T-SQL

Beneficial:

An understanding of data protection and information governance including GDPR and the importance of reporting standards and report definitions
Understanding of Business Intelligence terminology and processes
An understanding of terminology applicable to medical research
An understanding of Public sector / Government

BI, BUSINESS INTELLIGENCE, EXCEL, DASHBOARD, REPORTS, DATA, SQL, QLIK, QLIKVIEW, QLIK SENSE, TABLEAU, POWER BI, POWERBI, SQL, TSQL, T-SQL, GDPR

Hays Specialist Recruitment Limited acts as an employment agency for permanent recruitment and employment business for the supply of temporary workers. By applying for this job you accept the T&C's, Privacy Policy and Disclaimers which can be found at (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.