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For Companies At a Glance
- Tasks: Unlock data value, drive insights, and create impactful dashboards.
- Company: Join a leading player in the Pension and Asset Management market.
- Benefits: Competitive salary, career growth, and a dynamic work environment.
- Why this job: Make a real impact in financial services with your analytical skills.
- Qualifications: Strong Python skills and experience with BI tools required.
- Other info: Collaborative team atmosphere with opportunities for advanced analytics.
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
- 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 - Miryco Consultants Ltd 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 - Miryco Consultants Ltd in London
✨Tip Number 1
Network like a pro! Reach out to people in the financial services sector, especially those working in pensions and asset management. 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 Python projects and data visualisations. This is your chance to demonstrate how you can turn complex datasets into actionable insights, just like the role requires.
✨Tip Number 3
Prepare for interviews by brushing up on your knowledge of BI tools and financial datasets. Be ready to discuss how you've used these in past roles, and don’t forget to highlight your problem-solving skills!
✨Tip Number 4
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 - Miryco Consultants Ltd in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with Python and any relevant BI tools. We want to see how your skills align with the role, so don’t be shy about showcasing your achievements in financial services!
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 pensions and asset management sector. Let us know how you can contribute to our team and drive insights.
Showcase Your Technical Skills: Be specific about your technical abilities, especially with Python, SQL, and any BI tools you've used. We love seeing examples of how you've transformed complex datasets into actionable insights or visualisations.
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 makes the process smoother for everyone involved!
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 Scenario Questions
Expect questions that ask you to solve real-world problems using data. Practice explaining how you would approach transforming complex datasets into actionable insights, and be ready to showcase your problem-solving skills with specific examples.
✨Showcase Your Communication Skills
As a Business Intelligence Analyst, you'll need to translate data into business insights. Prepare to demonstrate how you’ve effectively communicated findings to stakeholders in the past, perhaps through dashboards or reports, to highlight your ability to make data accessible.
