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- Tasks: Lead data evaluation and annotation systems for AI-driven products at Bloomberg.
- Company: Join Bloomberg, a leader in data and financial technology innovation.
- Benefits: Competitive salary, health benefits, and opportunities for professional growth.
- Other info: Dynamic team environment with a focus on innovation and collaboration.
- Why this job: Make a real impact on AI-driven workflows and enhance user experiences with data.
- Qualifications: 4+ years in data product ownership and strong skills in SQL or Python.
The predicted salary is between 60000 - 80000 £ per year.
Bloomberg runs on data. Our products are fueled by powerful information. We combine data and context to paint the whole picture for our clients, around the clock - from around the world. In Data, we are responsible for delivering this data, news, and analytics through innovative technology - quickly and accurately. We apply problem‑solving skills to identify workflow efficiencies and implement technology solutions to enhance our systems, products, and processes.
The Bloomberg Data AI group brings innovative AI technologies into Bloomberg’s Data organization while supplying deep financial domain expertise to the development of AI‑powered products. The Code Generation Data Team provides strategic data management solutions for AI/ML systems that perform code generation. We partner closely with cross functional team members to align AI innovation with Bloomberg’s strategic objectives, focusing on optimizing data workflows and elevating the quality, intelligence, and usability of the data that drives our products.
We are seeking a Data Product Owner to lead the evaluation, annotation, and data quality systems underpinning the Enterprise Data Agent. As Bloomberg expands its enterprise data offerings, enabling users to efficiently discover, understand, and interact with data is increasingly critical. The Enterprise Data Agent is a strategic product designed to improve how users explore datasets, surface insights, and interact with Bloomberg’s enterprise data commercial offerings through AI‑driven workflows.
A key component of this product is ensuring that AI‑driven experiences are accurate, reliable, and continuously improving. This requires robust evaluation frameworks, high‑quality annotation systems, and measurable feedback loops. This role goes beyond traditional product ownership as you will act as the owner of the evaluation data layer, responsible for ensuring that user interactions, feedback, and annotated datasets translate into high‑quality signals for model improvement and product performance.
You will take ownership of fragmented, manual processes and transform them into scalable, repeatable, and measurable systems that support both human‑in‑the‑loop workflows and automated evaluation.
We’ll Trust You To
- Own and scale evaluation and annotation workflows, transforming fragmented processes into reliable, high‑signal pipelines
- Define and operate a release evaluation framework, ensuring consistent, human‑validated signals on product and model quality
- Drive development of automated evaluation (auto‑eval) to improve scalability and reduce manual dependency
- Establish and manage error and theme taxonomies, enabling structured, actionable insights for product and engineering
- Translate user feedback and evaluation outputs into prioritized product improvements, partnering closely with Engineering and Product
- Define, track, and report on key performance metrics, ensuring transparency into data quality and product performance
You’ll Need To Have
- 4+ years of experience in data product ownership, data operations, or AI/data evaluation workflows
- Strong understanding of data quality, data modeling, and AI evaluation methodologies
- Experience working with annotation workflows, labeled datasets, or human‑in‑the‑loop systems
- Proven ability to translate ambiguous problems into structured frameworks and processes
- Experience collaborating with engineering and product teams on AI/ML‑driven products
- Proficiency in SQL, Python, or similar tools for data analysis and validation
- Strong organizational and prioritization skills, with the ability to manage both strategic and operational responsibilities
We’d Love To See
- Experience with search, retrieval, or agent‑based AI systems
- Familiarity with evaluation frameworks for generative AI or LLM‑based products
- Experience designing taxonomies, ontologies, or structured labeling systems
- Understanding of enterprise data products and user workflows
- Experience working with data discovery platforms or metadata systems
- Knowledge of Bloomberg Enterprise Data
- Experience in Agile/Scrum environments
If indicated, please note that years of experience are a guide; we will consider applications from all candidates who can demonstrate the skills necessary for the role.
Senior Data Management Professional - Data Product Owner – Enterprise Data Agent in London employer: Bloomberg
Contact Detail:
Bloomberg Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Data Management Professional - Data Product Owner – Enterprise Data Agent in London
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, especially those at Bloomberg. A friendly chat can open doors and give you insights that a job description just can't.
✨Tip Number 2
Prepare for interviews by diving deep into Bloomberg's products and data management strategies. Show us you know your stuff and how you can contribute to our innovative AI-driven workflows.
✨Tip Number 3
Practice your problem-solving skills! Be ready to tackle real-world scenarios related to data quality and evaluation frameworks. We love candidates who can think on their feet and offer actionable solutions.
✨Tip Number 4
Don't forget to apply through our website! It’s the best way to ensure your application gets the attention it deserves. Plus, we’re always looking for passionate individuals to join our team!
We think you need these skills to ace Senior Data Management Professional - Data Product Owner – Enterprise Data Agent in London
Some tips for your application 🫡
Tailor Your Application: Make sure to customise your CV and cover letter for the Data Product Owner role. Highlight your experience with data quality, AI evaluation workflows, and any relevant projects that showcase your skills. We want to see how you fit into our world!
Showcase Your Problem-Solving Skills: In your application, don’t just list your skills; demonstrate how you've tackled ambiguous problems in the past. We love candidates who can turn challenges into structured solutions, so share specific examples that highlight your analytical thinking.
Highlight Collaboration Experience: Since this role involves working closely with engineering and product teams, make sure to mention any collaborative projects you've been part of. We value teamwork, so let us know how you've contributed to successful outcomes in cross-functional settings.
Apply Through Our Website: We encourage you to submit your application through our website. It’s the best way for us to receive your details and ensures you’re considered for the role. Plus, it shows you’re keen on joining our team at Bloomberg!
How to prepare for a job interview at Bloomberg
✨Know Your Data Inside Out
Make sure you have a solid understanding of data quality, data modelling, and AI evaluation methodologies. Brush up on your SQL and Python skills, as you'll likely be asked to demonstrate your proficiency in these areas during the interview.
✨Showcase Your Problem-Solving Skills
Prepare to discuss how you've tackled ambiguous problems in the past. Think of specific examples where you've transformed fragmented processes into structured frameworks, especially in data product ownership or AI workflows.
✨Understand the Role of User Feedback
Be ready to explain how user interactions and feedback can drive product improvements. Highlight any experience you have with human-in-the-loop systems and how you've used feedback loops to enhance data quality and product performance.
✨Familiarise Yourself with Bloomberg's Data Products
Do your homework on Bloomberg’s enterprise data offerings and the specific challenges they face. Understanding their products and how they leverage AI will help you align your answers with their strategic objectives during the interview.