At a Glance
- Tasks: Join a dynamic team to build machine-learning models and analyse economic data.
- Company: Bloomberg, a leading global financial services firm with a focus on innovation.
- Benefits: Competitive salary, diverse workplace, and opportunities for professional growth.
- Other info: Collaborative environment with a commitment to diversity and inclusion.
- Why this job: Make an impact in economics using cutting-edge technology and data science.
- Qualifications: 5+ years in quantitative analysis, strong Python skills, and a degree in a quantitative field.
The predicted salary is between 60000 - 80000 £ per year.
Location: London
Business Area: Research
Ref #: 10051727
With 70 economists and analysts and 200 economics and government reporters worldwide, Bloomberg has an outstanding capacity to explain where the world is economically and politically, where it might be heading, and the ways in which geopolitical and economic forces interact. Bloomberg Economics offers a comprehensive macroeconomic research service for Terminal subscribers. That includes analysis of major data releases and economic events, detailed forecasts, geo-economic research, and sophisticated modeling. The goal is to offer Bloomberg clients a deeper insight into the themes that drive policy, financial markets, and capital flows.
We’re seeking a data scientist or quantitative analyst with deep experience in narrative economics, machine learning and artificial intelligence to join our team in London.
The role
The successful candidate will work with Bloomberg’s economic modeling team to build and maintain machine‑learning models, data pipelines, and other analytical tools to support research. You’ll help turn text and other unstructured datasets into usable economic and geopolitical signals. Work on models and tools for tasks such as sentiment analysis, signal extraction, classification, and index construction. Build and manage pipelines to organize data, automate analysis, and support regular publication of results. You’ll also have opportunities to contribute to high‑priority research and analysis, either independently or in collaboration with colleagues. We’ll measure success by the quality of the analysis, the reliability of the models, the efficiency of development, and your overall contribution to the broader research agenda.
We’ll trust you to
- Build robust Python workflows for data analysis, modeling, and research production.
- Support colleagues in developing models, indicators, and other analytical outputs.
- Work with structured and unstructured data, including news, text, market, and economic datasets.
- Evaluate models carefully and communicate trade‑offs clearly with colleagues and stakeholders.
- Provide ad hoc analytical support to high‑priority research projects.
You’ll need to have
- 5+ years of experience in a role involving quantitative analysis, data science, and machine learning for economic and financial research.
- A degree in a quantitative subject.
- Experience building models, data pipelines, and other analytical tools using real‑world datasets.
- Strong Python skills, including experience with data analysis and modeling libraries.
- A solid understanding of statistics, machine learning, and deep learning, with the skills needed to conduct model evaluation and interpret black‑box model results.
- Knowledge of SQL or a keen interest in learning.
- Strong communication skills in English.
- The energy and initiative to advance simultaneous projects on tight deadlines.
We’d love to see
- Experience applying cutting‑edge techniques in machine learning or NLP to economic, financial, news or geopolitical data.
- Working knowledge of machine learning, NLP, and data engineering tools, with experience using frameworks such as scikit‑learn, PyTorch, Hugging Face, spaCy, or similar technologies.
- Experience working with alternative, unstructured or large‑scale datasets.
- Experience building dashboards or visualizations with libraries such as Streamlit or Plotly.
Bloomberg is an equal opportunity employer and we value diversity at our company. We do not discriminate on the basis of age, ancestry, color, gender identity or expression, genetic predisposition or carrier status, marital status, national or ethnic origin, race, religion or belief, sex, sexual orientation, sexual and other reproductive health decisions, parental or caring status, physical or mental disability, pregnancy or parental leave, protected veteran status, status as a victim of domestic violence, or any other classification protected by applicable law. Bloomberg is a disability inclusive employer. Please let us know if you require any reasonable adjustments to be made for the recruitment process.
Bloomberg Economics Data Scientist London, GBR Posted today employer: Bloomberg L.P.
Bloomberg is an exceptional employer, offering a dynamic work environment in the heart of London where innovation meets economic analysis. With a strong emphasis on employee growth, Bloomberg provides access to cutting-edge tools and technologies, fostering a culture of collaboration and diversity. Employees are encouraged to contribute to high-priority research projects, ensuring that their work has a meaningful impact on global economic understanding.
StudySmarter Expert Advice🤫
We think this is how you could land Bloomberg Economics Data Scientist London, GBR Posted today
✨Tip Number 1
Network like a pro! Reach out to current or former Bloomberg employees on LinkedIn. A friendly chat can give you insider info and maybe even a referral, which can really boost your chances.
✨Tip Number 2
Show off your skills! Prepare a portfolio showcasing your data science projects, especially those involving machine learning and economic analysis. This will help you stand out during interviews and demonstrate your expertise.
✨Tip Number 3
Practice makes perfect! Get ready for technical interviews by brushing up on Python and machine learning concepts. Use platforms like LeetCode or HackerRank to sharpen your coding skills and tackle real-world problems.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen. Plus, it shows you’re genuinely interested in joining the Bloomberg team. Don’t miss out on this opportunity!
We think you need these skills to ace Bloomberg Economics Data Scientist London, GBR Posted today
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the role of a Data Scientist at Bloomberg. Highlight your experience with machine learning, Python, and any relevant projects that showcase your skills in narrative economics and data analysis.
Craft a Compelling Cover Letter:Your cover letter should tell us why you're the perfect fit for this role. Share specific examples of your work with unstructured data and how you've used it to derive economic insights. Make it personal and engaging!
Showcase Your Technical Skills:Don’t forget to emphasise your technical skills! Mention your proficiency in Python, SQL, and any machine learning frameworks you’ve worked with. We want to see how you can contribute to our analytical tools and models.
Apply Through Our Website:We encourage you to apply through our website for a smoother application process. It’s the best way for us to receive your application and ensure it gets the attention it deserves!
How to prepare for a job interview at Bloomberg L.P.
✨Know Your Stuff
Make sure you brush up on your knowledge of machine learning, NLP, and economic data analysis. Be ready to discuss specific projects you've worked on, especially those involving Python and real-world datasets. This will show that you not only understand the theory but can also apply it practically.
✨Showcase Your Communication Skills
Since you'll be working with colleagues and stakeholders, it's crucial to demonstrate your ability to communicate complex ideas clearly. Prepare to explain your past work in a way that's easy to understand, focusing on how your contributions made a difference in previous projects.
✨Prepare for Technical Questions
Expect to face technical questions related to model evaluation, data pipelines, and statistical methods. Brush up on your SQL skills and be ready to discuss how you've used various libraries like scikit-learn or PyTorch in your work. Practising coding problems can also help you feel more confident.
✨Be Ready to Discuss Current Trends
Stay updated on the latest trends in economics and data science. Being able to discuss recent developments in machine learning or geopolitical events will show your passion for the field and your ability to connect your work to broader economic themes.