Senior Data Analyst...

EASYWEBRECRUITMENT.COM
Bradford
1 month ago
Applications closed

Related Jobs

View all jobs

Senior Data Analyst

Senior Data Analyst

Senior Data Analyst

Senior Data Analyst

Senior Data Analyst

Senior Data Analyst

Job Description

A place to drive change

Location: Bradford or Peterborough, Hybrid with travel as required.
Salary: £46,022 per annum
Permanent, 35 hours per week, Monday – Friday 9am to 5pm.

Our client is on a journey of transformation. They're finding new ways to achieve their purpose of providing families with affordable, sustainable and safe homes. They're innovating for their customers and to create a thriving workspace that supports everyone.

They're a team of passionate, dedicated people, working to drive change for the better. They're building something special here and they want driven, creative people to join them.

If you’re looking for a career where you can be part of change, share your ideas and help them transform, there’s never been a more exciting time to join them and shape their future.

About the role

Ready to turn data into decisions that shape the future?

Our client is on an exciting journey to transform how they understand and serve their customers. They're looking for a Senior Data Analyst who thrives on curiosity, stakeholder engagement, and delivering tangible value – not just building dashboards, but driving real outcomes. You’ll play a critical role in shaping their customer strategy and operational excellence. Your insights will directly influence service improvements and customer satisfaction. This isn’t about reporting for reporting’s sake, it’s about moving the dial and enabling proactive decision-making.

What you’ll do

• Lead performance reporting that drives strategic decisions.
• Develop predictive models to anticipate customer needs.
• Enable and evolve our data platform and CRM capabilities.
• Collaborate with internal stakeholders to ensure data-driven influence across the organisation.
• Help build a data community – knowledge sharing, external speakers, and fresh ideas welcome.

About you:

• Proven experience in data analysis with a strong track record of creating performance reports and predictive models.
• Strong experience with data visualisation and business intelligence tools (e.g., Power BI, Tableau, Qlik)
• Demonstrated ability to build predictive models using statistical or machine learning techniques.
• Experience working with large datasets, preferably in the housing, public sector, or not for profit sector.
• Excellent analytical and problem-solving skills with a customer-centric mindset.
• Strong communication skills with the ability to present complex findings to senior stakeholders and non-technical audiences.
• Ability to work independently, manage multiple priorities, and deliver high-quality work to deadlines.
• Degree or experience in Data Science, Statistics, Business Analytics, Mathematics, or a relevant experience.
• Experience in predictive analytics, forecasting, or machine learning applications in a business context.
• Knowledge of data protection regulations (GDPR) and best practices.

A place to build a future

They have big ambitions. That means they need people who are driven to succeed and eager to grow. Here, you’ll have the opportunity to learn new skills, thrive in their collaborative environment, and take your career in different directions. They also support your health and wellbeing with 28 days of holiday plus bank holidays (pro rata for part time) - an extra day’s leave to celebrate your birthday and the option to purchase more - a cash health plan, access to an online GP, gym discounts, and a dedicated day to volunteer for a cause that matters to you.

And because they believe in supporting you now and in the future, this is a place to plan for your future - with access to both Defined Contribution and Defined Benefit pension schemes through salary sacrifice, helping you save more efficiently. They also provide life assurance at three times your salary for all colleagues, giving you added peace of mind.

They're committed to making their recruitment process accessible and inclusive. If you require reasonable adjustments to any part of their recruitment process, please let them know they will ensure requirements are met.

Please don’t delay in submitting your application. Where roles are urgent or they receive a high volume of applications, they may interview and conclude the process prior to any closing date indicated.

Please note candidates must have current eligibility to live and work in the UK, they do not currently hold a sponsorship license.

If you’re looking for a place you can make a positive difference to society, to their organisation and to your future, apply now.  

Recruitment Agencies: They work exclusively with partners on their preferred supplier list (PSL) and do not accept unsolicited CVs or speculative approaches from agencies for this role.

You may have experience of the following: Senior Data Analyst, Data Analyst, Senior Analyst, Business Intelligence Analyst, BI Analyst, Insight Analyst, Predictive Analytics Analyst, Data Insights Analyst, Reporting Analyst, Performance Analyst, etc.

REF-225 238

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.

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

Are you considering a career change into machine learning in your 30s, 40s or 50s? You’re not alone. In the UK, organisations across industries such as finance, healthcare, retail, government & technology are investing in machine learning to improve decisions, automate processes & unlock new insights. But with all the hype, it can be hard to tell which roles are real job opportunities and which are just buzzwords. This article gives you a practical, UK-focused reality check: which machine learning roles truly exist, what skills employers really hire for, how long retraining realistically takes, how to position your experience and whether age matters in your favour or not. Whether you come from analytics, engineering, operations, research, compliance or business strategy, there is a credible route into machine learning if you approach it strategically.

How to Write a Machine Learning Job Ad That Attracts the Right People

Machine learning now sits at the heart of many UK organisations, powering everything from recommendation engines and fraud detection to forecasting, automation and decision support. As adoption grows, so does demand for skilled machine learning professionals. Yet many employers struggle to attract the right candidates. Machine learning job adverts often generate high volumes of applications, but few applicants have the blend of modelling skill, engineering awareness and real-world experience the role actually requires. Meanwhile, strong machine learning engineers and scientists quietly avoid adverts that feel vague, inflated or confused. In most cases, the issue is not the talent market — it is the job advert itself. Machine learning professionals are analytical, technically rigorous and highly selective. A poorly written job ad signals unclear expectations and low ML maturity. A well-written one signals credibility, focus and a serious approach to applied machine learning. This guide explains how to write a machine learning job ad that attracts the right people, improves applicant quality and strengthens your employer brand.

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

Machine learning job adverts in the UK love vague phrases like “strong maths” or “solid fundamentals”. That can make the whole field feel gatekept especially if you are a career changer or a student who has not touched maths since A level. Here is the practical truth. For most roles on MachineLearningJobs.co.uk such as Machine Learning Engineer, Applied Scientist, Data Scientist, NLP Engineer, Computer Vision Engineer or MLOps Engineer with modelling responsibilities the maths you actually use is concentrated in four areas: Linear algebra essentials (vectors, matrices, projections, PCA intuition) Probability & statistics (uncertainty, metrics, sampling, base rates) Calculus essentials (derivatives, chain rule, gradients, backprop intuition) Basic optimisation (loss functions, gradient descent, regularisation, tuning) If you can do those four things well you can build models, debug training, evaluate properly, explain trade-offs & sound credible in interviews. This guide gives you a clear scope plus a six-week learning plan, portfolio projects & resources so you can learn with momentum rather than drowning in theory.