At a Glance
- Tasks: Analyse data to uncover insights and trends, presenting findings to stakeholders.
- Company: Join a leading firm in the insurance and financial services sector.
- Benefits: Enjoy a competitive pension scheme, annual bonuses, and private medical insurance.
- Other info: Flexible holiday options and opportunities for professional growth.
- Why this job: Make an impact by transforming data into actionable insights in a collaborative environment.
- Qualifications: Degree or diploma in a numerical field; coding experience in SQL and Python required.
The predicted salary is between 30000 - 40000 £ per year.
We prefer candidates with a degree, apprenticeship, or diploma in a numerical discipline such as Mathematics, Statistics, or Data Science. Experience in coding, particularly with SQL and Python, is essential, though other languages are also welcome.
Technical Skills
- Advanced experience with Power BI: Creating and publishing dashboards, data transformation, visual conformity, and DAX formulas.
- Advanced Excel skills: Proficiency with functions including Lookups, Index, Match, Pivot Tables, and visualisations.
- Advanced SQL expertise: Proficient in reading and writing SQL code.
- Experience handling unstructured data: Capable of processing, conforming, and presenting large datasets (1M+ rows).
- Proficiency with the Microsoft O365 suite.
- Snowflake experience: Proficient in managing and manipulating data with Snowflake (and/or SQL) and connecting datasets to Power BI dashboards.
- Strong data analysis skills: Ability to understand, visualise, and trend large datasets to formulate evidence-based hypotheses and communicate findings to stakeholders.
- Data Science / Predictive Modelling: Skilled in using techniques to model past data for future predictions and understanding drivers of trends and patterns (preferable).
Non-Technical Skills
- Proven experience interacting directly with stakeholders.
- Ability to work collaboratively within a team to deliver projects.
- Comfort engaging with stakeholders at all levels.
- Adherence to agreed time‑frames, whether internal or regulatory.
- Understanding of data regulations such as PII, GDPR, and Data Retention.
- Ability to present data and communicate complex technical concepts clearly to non‑technical audiences.
- Experience in insurance or financial services (preferred).
- Prior experience working as part of a data team (preferred).
Benefits
- 12% defined non‑contributory pension scheme.
- Annual company bonus.
- Private medical insurance.
- Option to buy up to an additional 20 days or sell some of your holiday.
Working Hours
Data Analyst employer: Zurich Community Trust
As a Data Analyst at our company, you will thrive in a dynamic work culture that values collaboration and innovation. We offer a competitive benefits package, including a generous pension scheme and private medical insurance, alongside ample opportunities for professional growth and development in the heart of the financial services sector. Join us to make a meaningful impact while enjoying a supportive environment that encourages your career advancement.
StudySmarter Expert Advice🤫
We think this is how you could land Data Analyst
✨Tip Number 1
Network like a pro! Reach out to your connections in the data field, attend meetups, and join online forums. The more people you know, the better your chances of landing that Data Analyst role.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving SQL, Python, and Power BI. This will give potential employers a taste of what you can do and set you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and soft skills. Be ready to discuss your experience with data analysis, stakeholder engagement, and how you handle large datasets. Practice makes perfect!
✨Tip Number 4
Don't forget to apply through our website! We love seeing candidates who are genuinely interested in joining our team. Plus, it’s a great way to ensure your application gets noticed.
We think you need these skills to ace Data Analyst
Some tips for your application 🫡
Show Off Your Skills:Make sure to highlight your technical skills in SQL, Python, and Power BI. We want to see how you've used these tools in real projects, so don’t hold back on the details!
Tailor Your Application:Customise your CV and cover letter to match the job description. Use keywords from the listing to show us you’re a perfect fit for the Data Analyst role. It helps us see how your experience aligns with what we need.
Be Clear and Concise:When writing your application, keep it straightforward. We appreciate clarity, so avoid jargon and make sure your points are easy to understand. Remember, we want to know about your achievements without wading through fluff!
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it’s super easy!
How to prepare for a job interview at Zurich Community Trust
✨Know Your Numbers
Brush up on your numerical skills and be ready to discuss your academic background in Mathematics, Statistics, or Data Science. Be prepared to share specific examples of how you've applied these skills in real-world scenarios.
✨Show Off Your Coding Skills
Make sure you can confidently talk about your experience with SQL and Python. Consider preparing a small project or example that showcases your coding abilities, especially if it involves data manipulation or analysis.
✨Master Power BI and Excel
Familiarise yourself with creating dashboards in Power BI and using advanced Excel functions. You might be asked to demonstrate your knowledge, so practice building a sample dashboard or performing complex data analyses to showcase your skills.
✨Communicate Clearly
Prepare to explain complex data concepts in simple terms. Think about how you would present your findings to non-technical stakeholders, as this is crucial for the role. Practising with friends or family can help you refine your communication style.
