At a Glance
- Tasks: Develop predictive models and analyse complex datasets to drive key business decisions.
- Company: A modern, data-driven insurance provider with a collaborative and innovative culture.
- Benefits: Hybrid working, fast career progression, and opportunities for international work.
- Other info: Join a supportive team focused on learning and development.
- Why this job: Make a real impact in a high-growth environment while developing your data science skills.
- Qualifications: Strong STEM background, programming skills in Python, and a passion for data science.
The predicted salary is between 28000 - 38000 £ per year.
The Company
They are a modern, data-driven insurance provider focused on delivering flexible, tailored policies to customers. The business has expanded its product offering and built strong commercial partnerships, driving rapid growth. With around 100 employees, they are scaling quickly and investing heavily in advanced analytics and modelling. The culture is collaborative, fast-paced, and centred on innovation.
The Role
- As a Graduate Data Scientist, you will work on models that sit at the core of the business and support key commercial decisions.
- Develop predictive models across pricing, risk, and customer acquisition.
- Build clustering and segmentation models to support strategic decision‑making.
- Analyse large and complex datasets to uncover actionable insights.
- Collaborate with analysts and engineers to deploy and productionise models.
- Contribute to a greenfield modelling environment and help shape best practices.
- Take ownership of projects with visibility across the wider business.
Your Skills and Experience
- Strong academic background in a STEM subject such as Mathematics, Data Science, Computer Science, or similar.
- Solid programming skills, ideally in Python.
- Understanding of statistical modelling and machine learning fundamentals.
- Hands‑on experience through internships, placements, or personal projects.
- Demonstrated curiosity and initiative, such as side projects or GitHub work.
- Clear communication skills and the ability to collaborate with cross‑functional teams.
- Motivated, proactive, and keen to take ownership early in your career.
What They Offer
- Hybrid working with a strong in‑office culture.
- Opportunity to work on high‑impact, business‑critical models.
- Fast career progression as the team continues to grow.
- Work abroad flexibility for short periods each year.
- Supportive environment with strong learning and development opportunities.
How to Apply
If you are a graduate or early‑career data scientist looking to make an impact in a high‑growth environment, please apply with your CV.
Graduate Data Scientist employer: Harnham
As a modern, data-driven insurance provider based in London, this company offers an exceptional work environment for Graduate Data Scientists. With a strong emphasis on collaboration and innovation, employees benefit from hybrid working arrangements, fast career progression, and opportunities to work on impactful projects that shape the future of the business. The supportive culture fosters continuous learning and development, making it an ideal place for early-career professionals eager to make a meaningful contribution.
StudySmarter Expert Advice🤫
We think this is how you could land Graduate 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 Harnham 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 Harnham.
✨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 Harnham.
✨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 Harnham’s career page, where your unique skills can shine in their entry-level data science openings!
We think you need these skills to ace Graduate Data Scientist
Some tips for your application 🫡
Show Off Your Data Skills:As you're aiming for an entry-level data science role at Harnham, 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 Harnham 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 Harnham
✨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!
