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- Tasks: Lead strategy and development of classification datasets to maximise their value.
- Company: A leading financial data provider based in London.
- Benefits: Competitive salary, flexible working options, and opportunities for professional growth.
- Why this job: Influence innovative data solutions and drive impactful decisions for clients.
- Qualifications: Over 4 years of experience in financial data and strong product management skills.
- Other info: Join a dynamic team in a fast-paced environment with great career prospects.
The predicted salary is between 36000 - 60000 £ per year.
A leading financial data provider in London is seeking a Data Product Owner to lead the strategy and development of their classification datasets. This role involves maximizing dataset value, enhancing delivery mechanisms, and ensuring data quality.
Ideal candidates will have over 4 years of experience in financial data and proven product management skills in a cross-functional environment. Join us to influence innovative data solutions for clients and drive impactful decisions.
Data Product Owner — Private Company Classifications in London employer: Bloomberg
Contact Detail:
Bloomberg Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Product Owner — Private Company Classifications in London
✨Tip Number 1
Network like a pro! Reach out to people in the financial data sector on LinkedIn or at industry events. A friendly chat can open doors that a CV just can't.
✨Tip Number 2
Showcase your expertise! Prepare a portfolio or case studies that highlight your experience in product management and data strategy. This will help you stand out during interviews.
✨Tip Number 3
Practice makes perfect! Conduct mock interviews with friends or use online platforms to refine your answers, especially around your experience with dataset value maximisation and quality assurance.
✨Tip Number 4
Apply through our website! We love seeing candidates who take the initiative. Plus, it gives you a chance to showcase your enthusiasm for the role right from the start.
We think you need these skills to ace Data Product Owner — Private Company Classifications in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience in financial data and product management. We want to see how your skills align with the role, so don’t be shy about showcasing relevant projects or achievements!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re passionate about data solutions and how you can contribute to our team. Keep it engaging and personal – we love to see your personality come through.
Showcase Your Cross-Functional Experience: Since this role involves working across different teams, make sure to highlight any cross-functional projects you've been part of. We’re looking for examples that demonstrate your ability to collaborate and drive results.
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 – just follow the prompts!
How to prepare for a job interview at Bloomberg
✨Know Your Data Inside Out
Make sure you’re well-versed in the classification datasets relevant to the role. Brush up on your financial data knowledge and be ready to discuss how you’ve maximised dataset value in previous roles.
✨Showcase Your Product Management Skills
Prepare examples that highlight your product management experience, especially in cross-functional teams. Think about specific projects where you led strategy and development, and be ready to explain your approach and the outcomes.
✨Understand the Company’s Vision
Research the company’s current data solutions and their impact on clients. Be prepared to discuss how you can contribute to enhancing delivery mechanisms and ensuring data quality in line with their goals.
✨Ask Insightful Questions
Prepare thoughtful questions that demonstrate your interest in the role and the company. Inquire about their current challenges with classification datasets or how they envision the future of their data solutions. This shows you’re proactive and engaged.
