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- Tasks: Join our team as a Graduate Data Analyst, conducting statistical analysis and developing predictive models.
- Company: Enstar is a leading global insurance group known for innovative legacy solutions in the insurance sector.
- Benefits: Enjoy a £700 wellness reimbursement, private medical insurance, and a supportive work environment.
- Why this job: Kickstart your career with hands-on experience in data analytics and machine learning within a dynamic company.
- Qualifications: Ideal candidates should have a degree in Data Science, Statistics, or a related quantitative field.
- Other info: This role offers structured development, mentoring, and a commitment to diversity and inclusion.
The predicted salary is between 26400 - 39600 £ per year.
Enstar, a leading global insurance group, is offering an exciting opportunity for a Graduate Data Analyst as part of its Emerging Talent Programme. Based in the UK, this paid graduate role is ideal for individuals with a passion for data and innovation, and a desire to grow within a dynamic and forward-thinking organisation.
Applicants should hold, or be on track to achieve, a degree in a quantitative subject such as Data Science, Machine Learning, Statistics, Mathematics, Computer Science, or a related field. Enstar is committed to supporting its graduates with excellent benefits, including a 10% employer pension contribution and a £700 annual wellness reimbursement.
This is your chance to develop your career within a company renowned for delivering intelligent, data-driven insurance solutions across the globe.
About the Role
Our Emerging Talent Programme at Enstar is designed to build a great foundation in data analytics and machine learning within the insurance industry. It combines technical training, real-world business exposure, and structured development to support a successful transition from education to career. Over two years, participants will take part in tailored learning opportunities, rotational placements, and mentoring to develop critical thinking, data proficiency, and cross-functional awareness.
Responsibilities
- Conducting statistical analysis and applying machine learning techniques to insurance and financial data
- Supporting data preparation and transformation for analytical purposes
- Developing, testing, and refining predictive models
- Presenting insights to stakeholders and translating analytical outputs into business context
- Collaborating with engineers and analysts across departments
- Contributing to projects related to responsible AI, governance, and compliance
Candidate Profile
Candidates should have or be expecting to achieve a degree in a subject area such as Data Science, Machine Learning, Statistics, Mathematics, Computer Science, or another quantitative field. Skills and knowledge required include:
- Familiarity with supervised and unsupervised learning (e.g. regression, classification, clustering)
- Basic experience in Python, R, or SQL, and familiarity with libraries such as Scikit-learn, TensorFlow, or PyTorch
- Experience with data visualisation tools such as Power BI or Tableau
- Awareness of data privacy, responsible AI, and ethical technology practices
- Ability to convey technical ideas clearly and work collaboratively
Development and Support
Our graduates follow a structured development framework that includes:
- Formal training aligned to a professional qualification
- Technical and behavioural skills workshops
- Real business assignments and rotations
- Regular feedback and access to mentoring from experienced professionals
We offer a comprehensive package to support wellbeing, financial planning, and professional development. Benefits include:
- £700 annual wellness reimbursement
- Private medical and dental insurance
- Health screening and wellbeing support
- Cycle to Work scheme and electric vehicle lease
- Employee Assistance Programme
- Volunteering days and inclusive events
Our Commitment to Inclusion
Enstar is committed to creating an inclusive, respectful, and accessible workplace. We support candidates from all backgrounds and provide support and adjustments throughout the recruitment process. Applicants who require accommodations are encouraged to let us know at any stage. Enstar is an equal opportunity employer. We believe diversity of thought and experience strengthens decision-making and performance.
Recruitment Process
- Online application
- Online assessment and recorded interview
- Virtual assessment centre
Required Documents
CV/Resume
Application Process
If you’re ready to launch your career in data analytics with a business that values growth, innovation, and professional development, APPLY TODAY.
Graduate Data Analyst at Enstar employer: HipHopTune Media
Contact Detail:
HipHopTune Media Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Graduate Data Analyst at Enstar
✨Tip Number 1
Familiarise yourself with the specific tools and technologies mentioned in the job description, such as Python, R, SQL, and data visualisation tools like Power BI or Tableau. Having hands-on experience or projects showcasing these skills can set you apart during the interview process.
✨Tip Number 2
Understand the insurance industry and how data analytics plays a role in it. Research Enstar's business model and recent developments to demonstrate your knowledge and enthusiasm for the company during interviews.
✨Tip Number 3
Prepare to discuss your understanding of ethical AI and data privacy, as these are key components of the role. Think of examples where you've considered these aspects in your work or studies, and be ready to share them.
✨Tip Number 4
Network with current or former employees of Enstar on platforms like LinkedIn. Engaging with them can provide valuable insights into the company culture and the role, and may even lead to a referral.
We think you need these skills to ace Graduate Data Analyst at Enstar
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant skills and experiences related to data analysis, machine learning, and any quantitative subjects. Use keywords from the job description to demonstrate your fit for the Graduate Data Analyst role.
Craft a Compelling Cover Letter: Write a cover letter that showcases your passion for data and innovation. Explain why you want to work at Enstar specifically and how your background aligns with their Emerging Talent Programme.
Showcase Technical Skills: In your application, emphasise your familiarity with programming languages like Python or R, and any experience with data visualisation tools such as Power BI or Tableau. Mention specific projects or coursework that demonstrate these skills.
Prepare for Online Assessment: Familiarise yourself with the types of questions you might encounter in the online assessment. Brush up on statistical analysis and machine learning concepts, as well as practice coding problems if applicable.
How to prepare for a job interview at HipHopTune Media
✨Understand the Role
Make sure you thoroughly understand the responsibilities of a Graduate Data Analyst at Enstar. Familiarise yourself with key concepts like statistical analysis, machine learning techniques, and data visualisation tools. This will help you answer questions confidently and demonstrate your genuine interest in the position.
✨Showcase Your Technical Skills
Be prepared to discuss your experience with programming languages such as Python, R, or SQL. Highlight any projects where you've applied supervised or unsupervised learning techniques. If you have experience with libraries like Scikit-learn or TensorFlow, make sure to mention that too!
✨Prepare for Scenario-Based Questions
Expect scenario-based questions that assess your problem-solving skills and ability to apply your knowledge in real-world situations. Think about how you would approach data preparation, model development, and presenting insights to stakeholders. Practising these scenarios can give you an edge during the interview.
✨Emphasise Collaboration and Communication
Enstar values teamwork and clear communication. Be ready to discuss examples of how you've worked collaboratively on projects and how you convey technical ideas to non-technical stakeholders. This will show that you can thrive in a cross-functional environment.
