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- Tasks: Deliver high-quality analytical services and drive data-driven decision making.
- Company: Believe housing, a supportive and inclusive organisation focused on transformation.
- Benefits: Competitive salary, up to 33 days leave, healthcare scheme, and flexible working.
- Why this job: Join a dynamic team and make a real impact with your data science skills.
- Qualifications: Experience in data analysis, statistical methods, and machine learning.
- Other info: Flexible working arrangements and a culture that encourages growth and development.
The predicted salary is between 37000 - 62000 £ per year.
Are you ready to be part of something extraordinary? Here at believe housing, we’re entering into one of the most exciting chapters in our story – a bold and ambitious period of transformation that will reshape how we think, work and create exceptional value and experiences for our customers and colleagues. This transformation will see us embrace new technologies, reimagine our services and unlock the potential across every part of the business. If you thrive in fast-moving environments, love solving real problems and want to help build something brilliant for our customers — this is your moment.
We believe in life without barriers, if you think you’d be great in the role, we want to hear from you. We’re interested in your skills, experience and personal values and we’re committed to being a supportive and inclusive employer.
A flexible approach that works for you
We’re a family‑friendly organisation, and we encourage everyone to ‘work the believe way’; keeping things simple, focusing on what matters and removing unnecessary tasks. Your working arrangements will be flexible, based on the needs of the role, our customers and your preferences (agreed with your manager). Our offices are in Seaham and Bishop Auckland, and this role will require an on‑site presence for part of the week.
About the role
As a Data Scientist, you will be a key contributor to delivering high‑quality analytical services that enable data‑driven decision making across the organisation. As an enthusiastic and service‑focused colleague, you will ensure the highest standards in data science delivery including data collection and processing, statistical analysis, predictive modelling, and the responsible use of machine learning and AI. You will identify opportunities to improve the generation of actionable data insights through analytical methods, providing training, guidance and feedback to colleagues to drive continuous improvement and deliver excellent service outcomes.
Your responsibilities will include:
- Work with the transformation programme and teams across the organisation, playing an active role in the data community to deliver robust analysis, practical insights, and measurable improvements to the business.
- Consult with business functions and customers to understand their analytical needs.
- Stay current with emerging data science trends and emerging technologies, particularly in AI and GenAI.
- Present analysis and recommendations through briefings, written reports, presentations and discussions tailored to technical and non‑technical audiences.
- Create impactful data visualisations, dashboards and reports that communicate complex information in a clear and accessible way.
- Translate analytical outputs into clear, actionable insight that informs business decisions.
- Drive innovation in algorithm design, optimisation, and the use of deep‑learning and AI where appropriate.
What’s on offer?
Our people are our greatest strength, and we’re committed to helping you grow, stay curious, and thrive. At believe housing, we’ve created a supportive, inclusive culture where ideas are welcomed and development is encouraged. Our customers are at the heart of everything we do, and we know that great experiences start with empowered colleagues. That’s why we offer a comprehensive range of benefits designed to support your wellbeing, motivate you, and help you do your best work. We offer a competitive salary of £43,074 to £44,420 per annum and:
- Up to 33 days annual leave, plus four volunteering days
- Access to our healthcare scheme
- Flexible working that supports your wellbeing
- A positive, inclusive culture where growth and development are genuinely encouraged
Apply now
If you share our values and believe you can bring something special to this role, we’d love to hear from you. We are a Disability Confident Employer. If you need any adjustments or support throughout the recruitment process, please let us know. Early applications are encouraged, as we may close the vacancy early if we receive a high volume of interest. Closing date: 23:59 on Sunday 29 March 2026. Applications must be submitted via our website.
Data Scientist employer: Believe Housing
Contact Detail:
Believe Housing Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist
✨Tip Number 1
Network like a pro! Reach out to current employees at believe housing on LinkedIn or other platforms. Ask them about their experiences and any tips they might have for your application process. It’s all about making connections!
✨Tip Number 2
Prepare for the interview by brushing up on your data science skills. Be ready to discuss your experience with statistical analysis, predictive modelling, and AI. Show us how you can bring value to the team with real examples from your past work.
✨Tip Number 3
Don’t just focus on technical skills; highlight your soft skills too! Being service-focused and a great communicator is key in this role. Think of ways you’ve successfully collaborated with others or solved problems in a team setting.
✨Tip Number 4
Finally, apply through our website! It’s the best way to ensure your application gets seen. Plus, it shows you’re serious about joining believe housing and being part of our exciting transformation journey.
We think you need these skills to ace Data Scientist
Some tips for your application 🫡
Show Your Passion: When you're writing your application, let your enthusiasm for data science shine through! We want to see how excited you are about using data to solve real problems and make a difference.
Tailor Your Application: Make sure to customise your application to reflect the specific skills and experiences that align with the Data Scientist role. Highlight your experience with data collection, statistical analysis, and any relevant technologies, especially AI and machine learning.
Be Clear and Concise: We appreciate clarity! Use straightforward language and structure your application well. This will help us understand your qualifications and how you can contribute to our transformation journey.
Apply Through Our Website: Don’t forget to submit your application via our website! It’s the best way for us to receive your details and ensures you’re considered for this exciting opportunity.
How to prepare for a job interview at Believe Housing
✨Know Your Data Science Stuff
Make sure you brush up on your data science skills, especially in areas like statistical analysis, predictive modelling, and machine learning. Be ready to discuss specific projects you've worked on and how you've used these techniques to solve real problems.
✨Understand the Company’s Vision
Dive into believe housing's mission and values. Familiarise yourself with their transformation goals and think about how your skills can contribute to their vision of creating exceptional value for customers. This will show your genuine interest in the role.
✨Prepare for Practical Scenarios
Expect to tackle practical scenarios during the interview. Think about how you would approach a data problem relevant to the company. Practising how to present your analysis and recommendations clearly will help you stand out, especially when addressing both technical and non-technical audiences.
✨Showcase Your Communication Skills
As a Data Scientist, you'll need to communicate complex information effectively. Prepare to demonstrate your ability to create impactful data visualisations and reports. Bring examples of your work that highlight your ability to translate analytical outputs into actionable insights.