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- Tasks: Monitor data controls and troubleshoot issues to support investment decisions.
- Company: Global investment organisation with a focus on data governance.
- Benefits: Hybrid work model, competitive salary, and opportunities for professional growth.
- Why this job: Join a team that shapes investment strategies through high-quality data management.
- Qualifications: Experience in data operations, strong analytical skills, and proficiency in SQL and Python.
- Other info: Collaborative environment with cross-functional teams and impactful projects.
The predicted salary is between 50000 - 70000 £ per year.
A global investment organization seeks a Data Analyst to enable high-quality investment decisions through data governance and management. In this hybrid role, you will monitor data controls, troubleshoot issues, and collaborate closely with cross-functional teams.
Ideal candidates have a background in data operations within investment management, strong analytical skills, and proficiency in SQL and Python. This opportunity offers the chance to contribute to a best-in-class data architecture that supports investment decision-making.
Investment Data Analyst — Hybrid, London employer: AustralianSuper
Contact Detail:
AustralianSuper Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Investment Data Analyst — Hybrid, London
✨Tip Number 1
Network like a pro! Reach out to professionals in the investment management field on LinkedIn. Join relevant groups and engage in discussions to get your name out there and learn about potential job openings.
✨Tip Number 2
Prepare for those interviews! Brush up on your SQL and Python skills, and be ready to discuss how you've used data to drive decisions in past roles. We want you to showcase your analytical prowess!
✨Tip Number 3
Don’t underestimate the power of follow-ups! After an interview, send a quick thank-you email to express your appreciation and reiterate your interest in the role. It keeps you fresh in their minds!
✨Tip Number 4
Apply through our website! We’ve got loads of opportunities waiting for you, and applying directly can sometimes give you an edge. Plus, it’s super easy to navigate!
We think you need these skills to ace Investment Data Analyst — Hybrid, London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience in data operations, especially within investment management. We want to see how your skills in SQL and Python can contribute to our data governance efforts.
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 help us make high-quality investment decisions. Be specific about your past experiences.
Showcase Your Analytical Skills: In your application, don’t forget to mention any projects or experiences that demonstrate your strong analytical skills. We love seeing how you've tackled data challenges in the past!
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 this exciting opportunity with our team.
How to prepare for a job interview at AustralianSuper
✨Know Your Data Inside Out
Make sure you brush up on your knowledge of data governance and management. Be prepared to discuss how you've previously monitored data controls and resolved issues, as this will show your practical experience in the field.
✨Show Off Your Analytical Skills
Prepare to demonstrate your analytical skills with real-world examples. Think about times when your analysis led to significant investment decisions or improvements in data processes. This will help you stand out as a candidate who can contribute meaningfully.
✨Get Comfortable with SQL and Python
Since proficiency in SQL and Python is key for this role, be ready to answer technical questions or even solve problems on the spot. Brush up on common queries and coding challenges that might come up during the interview.
✨Collaborate Like a Pro
This role involves working closely with cross-functional teams, so be prepared to discuss your teamwork experiences. Share examples of how you've successfully collaborated with others to achieve a common goal, especially in an investment management context.