Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Unlock data value and drive insights for investment decisions and client reporting.
- Company: Join a leading player in the Pension and Asset Management market.
- Benefits: Competitive salary, professional development, and a dynamic work environment.
- Why this job: Make a real impact by transforming complex data into actionable insights.
- Qualifications: Strong Python skills and experience in financial services preferred.
- Other info: Exciting opportunity for career growth in a modern data analytics team.
The predicted salary is between 36000 - 60000 £ per year.
Overview
Miryco is working with a leading player in the Pension and Asset Management market.
Job Specification: Business Intelligence Analyst
Department: Business Intelligence / Data Analytics
Sector: Pensions & Asset Management
About the Role
We are seeking a Business Intelligence Analyst to join our data and analytics team within a leading Pension & Asset Management organisation. This role will play a key part in unlocking the value of our data, driving insights that support investment decisions, client reporting, and operational efficiency. The ideal candidate will combine strong technical skills — particularly with Python — with a financial services (insurance, pensions or asset management preferred) environment.
Key Responsibilities
- Develop, maintain, and optimise datasets, using Python and other data tools.
- Collaborate with investment, risk, and operations teams to gather requirements and deliver actionable insights.
- Transform complex data sets into clear dashboards, visualisations, and reports for business stakeholders.
- Ensure data accuracy, governance, and security across reporting processes.
- Work with large datasets from multiple sources (investment, risk, client, operational) to create integrated analytical views.
- Contribute to the development of a modern data platform supporting advanced analytics and machine learning use cases.
- Support the migration of legacy reporting tools into Databricks and modern BI solutions.
Key Skills & Experience
Essential:
- Strong hands-on experience with Python.
- Solid knowledge of BI and data visualisation tools (e.g., Power BI, Tableau, Qlik).
- Strong SQL and data modelling skills.
- Experience working with large, complex financial datasets.
- Familiarity with cloud platforms (Azure / AWS / GCP) is an advantage.
- Knowledge of pensions, asset management, or wider financial services industry.
- Strong problem-solving, analytical, and communication skills — able to translate data into business insight.
Location: London
Finally, if you are not contacted within five working days of submitting your application, you have not been shortlisted for the opportunity. We will, however, be in touch should there be any other opportunities suited to your skills.
Business Intelligence Analyst - Financial Services in London employer: Jobster
Contact Detail:
Jobster Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Business Intelligence Analyst - Financial Services in London
✨Tip Number 1
Network like a pro! Reach out to people in the financial services sector, especially those working in business intelligence. A friendly chat can lead to insider info about job openings that aren't even advertised yet.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data visualisation projects or any dashboards you've built. This gives potential employers a taste of what you can do with Python and BI tools.
✨Tip Number 3
Prepare for interviews by brushing up on common BI scenarios. Be ready to discuss how you've transformed complex datasets into actionable insights. We want to see your problem-solving skills in action!
✨Tip Number 4
Don't forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, we love seeing candidates who take the initiative to connect directly with us.
We think you need these skills to ace Business Intelligence Analyst - Financial Services in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Business Intelligence Analyst role. Highlight your experience with Python, BI tools, and any relevant financial services background. We want to see how your skills match 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 analytics in the financial services sector. Share specific examples of how you've used your skills to drive insights and support decision-making.
Showcase Your Technical Skills: Don’t hold back on showcasing your technical prowess! Mention your hands-on experience with Python, SQL, and any BI tools you’ve worked with. We love seeing candidates who can demonstrate their ability to handle large datasets and create impactful visualisations.
Apply Through Our Website: We encourage you to apply through our website for a smoother application process. It helps us keep track of your application and ensures you’re considered for the right opportunities. Plus, it’s super easy!
How to prepare for a job interview at Jobster
✨Know Your Data Tools
Make sure you brush up on your Python skills and get familiar with BI tools like Power BI or Tableau. Be ready to discuss how you've used these tools in past projects, as this will show your technical prowess and relevance to the role.
✨Understand the Financial Landscape
Since this role is in the financial services sector, it’s crucial to have a solid understanding of pensions and asset management. Research current trends and challenges in the industry so you can speak knowledgeably about how your insights can drive investment decisions.
✨Prepare for Problem-Solving Questions
Expect to face questions that assess your analytical and problem-solving skills. Think of specific examples where you've transformed complex data into actionable insights, and be ready to explain your thought process clearly.
✨Showcase Your Communication Skills
As a Business Intelligence Analyst, you'll need to translate data into business insights for stakeholders. Practice explaining technical concepts in simple terms, and prepare to demonstrate how you've effectively communicated findings in previous roles.
