At a Glance
- Tasks: Analyse complex data and lead projects to drive business insights.
- Company: Dynamic company in London focused on innovation and diversity.
- Benefits: Competitive salary, inclusive culture, and opportunities for professional growth.
- Other info: Join a diverse team with a commitment to equity and inclusion.
- Why this job: Make a real impact by transforming data into actionable insights.
- Qualifications: Bachelor’s degree and experience in data analysis or IT.
The predicted salary is between 35000 - 45000 £ per year.
The Data Analyst is responsible for analytic data needs of the business unit. Handle complex data projects and acts as a lead for other Data Analysts.
Location: London - UK - Fenchurch
Job Responsibilities:
- Provide advanced analytical support for business operations in areas such as claims, client data, policy data, and external reporting.
- Extract, load, model, and reconcile large amounts of data across multiple system platforms and sources.
- Review data to determine operational impacts and needed actions; elevate issues, trends, areas for improvement and opportunities to management.
- Develop reports and deliverables for management.
- Model data using MS Excel, Access, SQL, and/or other data warehouse analytical tools.
- Ensure compliance with federal and state deliverable reporting requirements by performing data quality audits and analysis.
- Assist with training and mentoring other Data Analysts.
- Support Data systems as functional administrator evaluating new release functionality to include testing and implementation of new functionality.
- Perform other duties as assigned.
Work Experience and Education:
- Bachelor’s degree in related field or equivalent experience.
- 1+ years of statistical analysis or 1+ years of related IT experience, including data warehouse, coding or ETL experience.
- Experience managing projects or heavy involvement in project implementation.
- Experience in Data Visualization and building dashboards using SQL.
- Experience with coding languages such as Python or R.
- Experience in underwriting analysis.
Licenses & Certifications:
- Power BI Data Analyst Associate Certification (PL-300), or Tableau Certified Data Analyst a plus.
Skills:
- Technical/Functional Skills: Business Analytics, Data Governance, SQL, ETL Pipelines, Coding, Data Warehouse, Dashboards, Data Visualization, Ad hoc Reporting, Tableau, Power BI.
- Behavioral Skills: Analytical Thinking, Customer Service Management, Effective Communication, Organizational Skills, Problem Solving, Time Management.
Data Analyst in London employer: Ryan Specialty
At Ryan Specialty, we pride ourselves on being an exceptional employer, offering a dynamic work culture that fosters collaboration and innovation in the heart of London. Our commitment to employee growth is evident through comprehensive training programs and mentorship opportunities, ensuring that our Data Analysts not only excel in their roles but also advance their careers. With a focus on diversity and inclusion, we create an environment where every team member's contributions are valued, making it a truly rewarding place to work.
StudySmarter Expert Advice🤫
We think this is how you could land Data Analyst in London
✨Tip Number 1
Network like a pro! Reach out to your connections in the data field, attend meetups, and join online forums. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data projects, dashboards, and any coding work you've done. This gives potential employers a taste of what you can bring to the table.
✨Tip Number 3
Prepare for interviews by brushing up on common data analysis questions and scenarios. Practice explaining your thought process when tackling data problems, as this will highlight your analytical thinking skills.
✨Tip Number 4
Don't forget to apply through our website! We love seeing candidates who are genuinely interested in joining us at StudySmarter. Tailor your application to show how your skills align with our needs.
We think you need these skills to ace Data Analyst in London
Some tips for your application 🫡
Tailor Your CV:Make sure your CV speaks directly to the Data Analyst role. Highlight your experience with SQL, data visualisation, and any relevant projects you've managed. We want to see how your skills align with what we're looking for!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you're passionate about data analysis and how you can contribute to our team. Keep it concise but impactful – we love a good story!
Show Off Your Technical Skills:Don’t hold back on showcasing your technical prowess! Mention your experience with tools like Power BI, Tableau, and any coding languages you know. We’re keen to see how you can leverage these skills in our projects.
Apply Through Our Website:We encourage you to apply through our website for a smoother process. It helps us keep track of applications and ensures you don’t miss out on any important updates. Plus, it’s super easy!
How to prepare for a job interview at Ryan Specialty
✨Know Your Data Tools
Make sure you’re familiar with the tools mentioned in the job description, like SQL, Excel, and any data visualisation software. Brush up on your coding skills in Python or R, as these will likely come up during technical discussions.
✨Showcase Your Analytical Skills
Prepare to discuss specific examples of how you've used data analysis to drive business decisions. Think about times when you identified trends or areas for improvement and be ready to explain your thought process.
✨Practice Problem-Solving Scenarios
Expect to face some problem-solving questions during the interview. Practise explaining how you would approach a complex data project or troubleshoot an issue, as this will demonstrate your analytical thinking and organisational skills.
✨Communicate Effectively
Since effective communication is key in this role, practise articulating your thoughts clearly. Be prepared to explain technical concepts in a way that’s easy to understand, especially if you’ll be training or mentoring other analysts.
