At a Glance
- Tasks: Drive product development for unstructured datasets and enhance client solutions.
- Company: Bloomberg, a leader in financial technology with a focus on innovation.
- Benefits: Competitive salary, professional growth, and a dynamic work environment.
- Other info: Collaborative culture with opportunities to learn from industry experts.
- Why this job: Join a passionate team and shape the future of data analytics in finance.
- Qualifications: 5+ years in finance/tech, experience with unstructured data, and programming skills.
The predicted salary is between 70000 - 90000 £ per year.
Enterprise Data at Bloomberg provides machine-readable feeds of news and other unstructured content, as well as AI-powered analytics, including sentiment and more. Text is at the core of what we do today, with audio, imagery, and video increasingly in scope. Our client base includes major hedge funds, asset managers, and investment banks, typically using our feeds and analytics for low latency and intraday trading, market making, quantitative investing, and risk.
We’re looking for a charismatic Product Manager to join a growing team of technologists to help drive and execute on product development across our unstructured datasets. You’ll bring with you a few years working in a financial or technology firm in the machine learning/quantitative trading domain, along with some programming and data management skills. You’ll work alongside seasoned industry professionals, gaining personal development whilst contributing your strong technical skills and a positive, can-do attitude.
We’ll trust you to:
- Understand client needs, identify improvements and new use cases
- Contribute to defining product development plans across text and other unstructured datasets
- Drive engineering resources and execute planned development initiatives
- Evaluate new unstructured data sources and assess their quality, coverage, and product potential
- Create and update portfolios of client-facing technical documentation
- Design protocols and tools to facilitate comprehensive product quality checks
- Provide quantitative research to support client testing and onboarding
- Serve as subject matter expert in client discussions, sales meetings, industry events
You’ll need to have:
- Bachelor’s or graduate degree in business, finance, or engineering-related field
- 5+ years’ work experience in a financial or technology company
- Hands-on experience working with unstructured text data - for example NLP, text analytics, large news or document corpora, or LLM-based pipelines
- Knowledge of Python or SQL. Understanding of how ETL pipelines work a plus.
- Understanding of data structures, algorithms, machine learning, quantitative trading.
- Good written and verbal communication skills.
- Sense of humor a plus.
We’d love to see:
- Experience with non-text unstructured data: audio or speech, imagery, or video
- Familiarity with multimodal machine learning, embeddings, or modern foundation models
- Experience building or evaluating data labeling, annotation, or quality pipelines at scale
Enterprise Data- Unstructured Data Product Manager employer: Bloomberg
Bloomberg is an exceptional employer, offering a dynamic work environment in the heart of London where innovation meets finance. With a strong focus on employee growth, we provide opportunities for professional development alongside industry experts, fostering a collaborative culture that values creativity and technical expertise. Our commitment to cutting-edge technology and diverse datasets ensures that you will be at the forefront of the financial data landscape, making a meaningful impact in your role as an Enterprise Data Product Manager.
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We think this is how you could land Enterprise Data- Unstructured Data Product Manager
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We think you need these skills to ace Enterprise Data- Unstructured Data Product Manager
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
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How to prepare for a job interview at Bloomberg
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
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✨Get Comfortable with Python and R
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✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
