Data Analyst

Stanton by Bridge
2 months ago
Applications closed

Related Jobs

View all jobs

Data Analyst

Data Analyst

Data Analyst

Data Analyst

Data Analyst

Data Analyst

Data Analyst

Location: Derbyshire

Salary: Up to £30,000 per annum

Hours: 37.5 hours per week, full-time, permanent, Office based.

Are you a Data Analyst who enjoys turning raw data into insight that drives business decisions? Do you have strong Excel skills, experience working with an ERP system, and a keen eye for detail? If so, this could be the perfect next step for you.

This is a fantastic opportunity to join a forward-thinking organisation based in Derbyshire, offering exposure across both operational and commercial data functions. You’ll play a key role in ensuring accurate, efficient, and insightful reporting across multiple departments.

The Role

As a Data Analyst, you will:

Collect, validate and prepare data from different business systems to create clear and accurate reports.

Maintain and enhance data integrity across ERP systems such as AX, SL or similar.

Build and develop dashboards and reports using Power BI and advanced Excel techniques (formulas, pivot tables, lookups, etc).

Support the automation of manual reporting processes to improve efficiency and reliability.

Partner with colleagues across operations, retail, and manufacturing to ensure consistent reporting and analysis.

About You

We’re looking for someone who can bring a mix of technical skill and business understanding. You’ll need to have:

Strong Excel experience (formulas, pivot tables, data transformation).

Hands-on experience with an ERP system (AX, SL or similar).

Working knowledge of Power BI or a similar reporting tool.

Excellent attention to detail and a methodical approach to data accuracy.

Confidence handling and interpreting large datasets.

A collaborative mindset with clear communication skills across technical and non-technical teams.

Why Apply?

This Data Analyst role offers the chance to work in a supportive environment where data and insight are at the heart of decision-making. You’ll be encouraged to bring new ideas, streamline reporting, and help shape the way the business uses data.

If you’re an analytical thinker who loves working with systems, spreadsheets, and dashboards — and you’re looking to grow your career as a Data Analyst, Reporting Analyst, or Business Data Analyst - we’d love to hear from you.

Please note - this role is OFFICE BASED so only applications from candidates who live in the Derbyshire/Nottinghamshire area.

Apply today to take the next step in your data career.

EMA25

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.

Data Science Jobs for Career Switchers in Their 30s, 40s & 50s (UK Reality Check)

Thinking about switching into data science in your 30s, 40s or 50s? You’re far from alone. Across the UK, businesses are investing in data science talent to turn data into insight, support better decisions and unlock competitive advantage. But with all the hype about machine learning, Python, AI and data unicorns, it can be hard to separate real opportunities from noise. This article gives you a practical, UK-focused reality check on data science careers for mid-life career switchers — what roles really exist, what skills employers really hire for, how long retraining typically takes, what UK recruiters actually look for and how to craft a compelling career pivot story. Whether you come from finance, marketing, operations, research, project management or another field entirely, there are meaningful pathways into data science — and age itself is not the barrier many people fear.

How to Write a Data Science Job Ad That Attracts the Right People

Data science plays a critical role in how organisations across the UK make decisions, build products and gain competitive advantage. From forecasting and personalisation to risk modelling and experimentation, data scientists help translate data into insight and action. Yet many employers struggle to attract the right data science candidates. Job adverts often generate high volumes of applications, but few applicants have the mix of analytical skill, business understanding and communication ability the role actually requires. At the same time, experienced data scientists skip over adverts that feel vague, inflated or misaligned with real data science work. In most cases, the issue is not a lack of talent — it is the quality and clarity of the job advert. Data scientists are analytical, sceptical of hype and highly selective. A poorly written job ad signals unclear expectations and immature data practices. A well-written one signals credibility, focus and serious intent. This guide explains how to write a data science job ad that attracts the right people, improves applicant quality and positions your organisation as a strong data employer.

Maths for Data Science Jobs: The Only Topics You Actually Need (& How to Learn Them)

If you are applying for data science jobs in the UK, the maths can feel like a moving target. Job descriptions say “strong statistical knowledge” or “solid ML fundamentals” but they rarely tell you which topics you will actually use day to day. Here’s the truth: most UK data science roles do not require advanced pure maths. What they do require is confidence with a tight set of practical topics that come up repeatedly in modelling, experimentation, forecasting, evaluation, stakeholder comms & decision-making. This guide focuses on the only maths most data scientists keep using: Statistics for decision making (confidence intervals, hypothesis tests, power, uncertainty) Probability for real-world data (base rates, noise, sampling, Bayesian intuition) Linear algebra essentials (vectors, matrices, projections, PCA intuition) Calculus & gradients (enough to understand optimisation & backprop) Optimisation & model evaluation (loss functions, cross-validation, metrics, thresholds) You’ll also get a 6-week plan, portfolio projects & a resources section you can follow without getting pulled into unnecessary theory.