At a Glance
- Tasks: Build data pipelines and generate insights for impactful public sector projects.
- Company: Join a dynamic team at the forefront of data science and AI innovation.
- Benefits: Enjoy a competitive salary, hybrid working, and ongoing professional support.
- Other info: Great opportunity for growth in a supportive, inclusive environment.
- Why this job: Make a real difference by solving real-world problems with data.
- Qualifications: Experience in Python and data analysis; passion for learning and collaboration.
The predicted salary is between 40000 - 40000 £ per year.
We are looking for an early-career Data Scientist to join our team and support the development and delivery of a range of data-driven products used across the public sector.
Salary: £40,000
Location: Full time, hybrid. London Bridge SE1, with a mix of remote and office working
Closing date: 8 July 2026
This is a hands-on, production-focused role where you will contribute to the full lifecycle of data science—from building data pipelines through to generating insights and supporting live systems. You will work alongside experienced data scientists, software engineers, and product managers, with structured support as you build confidence working in production environments.
In your first year, your work will focus on developing and maintaining data pipelines, supporting existing digital products, and contributing to short-term projects to provide data-focussed support to non-technical teams. Over time, you will take increasing ownership of data science development backlogs for established products, while continuing to work as part of a collaborative team to deploy and manage changes safely.
This role is well suited to someone who enjoys solving real-world problems with data, is comfortable working across a range of technical tasks, and is interested in how emerging AI tools can transform the way data science is carried out.
The team you will join is a small, multidisciplinary team working at the intersection of data science, data engineering, and software development. Work is delivered in collaboration with product managers and stakeholders across the public sector, including the NHS, central government, and voluntary sector organisations. The team follows modern software development practices, including version control, code review, and CI/CD pipelines, ensuring that all changes to production systems are robust, tested, and delivered safely.
As an early-career member of the team, you will receive ongoing support and guidance while working on real systems used in operational settings. Given the small size of the team, there is an excellent opportunity for everyone to contribute to approaches and introduce new techniques, more so now than ever with rapid developments in AI.
Key responsibilities:- Build and extend data pipelines using Python, following established templates and patterns
- Contribute to the ingestion, transformation, and validation of data within a shared data platform
- Support the ongoing improvement of pipeline performance, reliability, and scalability
- Contribute to a collaborative development process using GitHub, including code review and version control
- Write clear, maintainable, tested and well-documented Python code suitable for production use
- Support testing and deployment activities within established CI/CD processes
- Support short-term projects with a focus on data by helping non-technical teams put data at the heart of end-to-end solutions
- Clean, analyse, and interpret data to generate insights for stakeholders
- Develop dashboards and visualisations (e.g. Power BI) to communicate findings clearly
- Respond to client user requests, such as queries about data outputs
- Work with stakeholders to understand requirements and improve existing products
- Stay informed about developments in data science and AI, exploring opportunities to improve ways of working
- Experience using Python for data analysis or data processing, including libraries such as pandas or NumPy
- Understanding of data analysis workflows, including data cleaning, transformation, and exploratory analysis
- Motivation to develop skills in working with production data systems and modern development practices
- Ability to communicate clearly with both technical and non-technical stakeholders
- Experience working with data pipelines or ETL processes
- Familiarity with version control (e.g. Git) and collaborative development workflows
- Exposure to CI/CD processes or deploying code into production environments
- Experience creating data visualisations or dashboards (e.g. Power BI, Tableau)
- Basic understanding of web applications or frameworks (e.g. Django)
- Previous experience (academic, professional, or personal) working on real-world data projects
- Strong problem-solving skills, with attention to detail and a willingness to debug issues
- Comfortable working as part of a team, with a willingness to learn from others and take on feedback
- Interest in emerging AI approaches, such as LLMs or workflow automation
We actively encourage applications from under-represented and minoritised groups, including those with lived experience of the social issues we are working to address. We are an equal opportunities employer.
Data Scientist employer: Social Finance Ltd
Join a dynamic team at the forefront of data science, where you will have the opportunity to work on impactful projects within the public sector. Our hybrid work model promotes a healthy work-life balance, while our collaborative culture fosters continuous learning and innovation, particularly in the exciting realm of AI. With structured support for your professional growth and the chance to contribute to meaningful solutions, this role is perfect for those eager to make a difference through data.
StudySmarter Expert Advice🤫
We think this is how you could land Data Scientist
✨Embrace Online Competitions
Get involved in online data science competitions like Kaggle or DrivenData. These platforms not only let you showcase your skills but also help you build a portfolio that stands out to hiring companies like Social Finance Ltd when you're aiming for that entry-level role.
✨Join Data Science Meetups
Look for local data science meetups or workshops happening in your area. These are perfect for connecting with industry professionals and fellow newbies, giving us the chance to learn the ropes and get our foot in the door at companies like Social Finance Ltd.
✨Networking Through University Career Services
Don't forget to leverage your university's career services! They often have exclusive internships and networking events specifically for entry-level data science positions. This is a golden opportunity to meet recruiters from companies like Social Finance Ltd.
✨Spotlight Your Skills Online
Create a strong online presence by sharing your projects and insights on platforms like GitHub or LinkedIn. Make sure to apply directly through Social Finance Ltd’s career page, where your unique skills can shine in their entry-level data science openings!
We think you need these skills to ace Data Scientist
Some tips for your application 🫡
Show Off Your Data Skills:As you're aiming for an entry-level data science role at Social Finance Ltd, don't forget to highlight your proficiency in programming languages like Python or R. Dive into your CV and mention any relevant projects or coursework that demonstrate your data analysis skills or machine learning knowledge.
Include Relevant Projects:If you've done any data-related projects, whether in your studies or during a personal quest, showcase them in a portfolio. This gives us a tangible sense of your capabilities and shows your hands-on experience with data manipulation, visualisation, or model building.
Tailor Your Cover Letter:When crafting your cover letter, make sure to express your enthusiasm for data science and how this role at Social Finance Ltd aligns with your career goals. Consider sharing why you’re drawn to data-driven decision-making and how you see yourself growing in this field.
Show Your Curiosity:In the data science world, curiosity is key! Mention any online courses or certifications you've pursued that complement your studies. This could be anything from a statistics certification to a data visualisation workshop. It shows us you're serious about learning and growing in this field.
How to prepare for a job interview at Social Finance Ltd
✨Brush Up on Your Statistics
For a data science role, the interview may involve some statistical questions or problems. Make sure you're comfortable with concepts like probability, distributions, and hypothesis testing. This will not only help you answer questions but also show your analytical thinking.
✨Get Hands-On with Tools
Familiarise yourself with popular data science tools like Python, R, and SQL. If you're asked about specific projects, be ready to discuss the tools you used and how they contributed to your analysis. Showing that you not only know the theory but can apply it is essential!
✨Showcase Relevant Projects
As an entry-level candidate, your portfolio is crucial. Bring along examples of data projects you've worked on, whether during your studies or personal projects. Discuss the challenges you faced and how you overcame them, highlighting your problem-solving skills.
✨Prepare for Case Studies
Entry-level interviews in data science often include case studies where you'll have to analyse a dataset or solve a problem on the spot. Try out some practice case studies beforehand, so you're not caught off guard. It's all about displaying your thought process and how you tackle data-driven challenges!
