At a Glance
- Tasks: Build and maintain machine-learning models and data pipelines for economic research.
- Company: Join Bloomberg, a leader in economic analysis and data-driven insights.
- Benefits: Competitive salary, diverse workplace, and opportunities for professional growth.
- Other info: Collaborative environment with a focus on innovation and cutting-edge technology.
- Why this job: Make an impact by turning complex data into actionable economic insights.
- Qualifications: 5+ years in quantitative analysis, strong Python skills, and a degree in a quantitative field.
The predicted salary is between 70000 - 90000 £ per year.
Location: London
Business Area: Research
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 London where innovation meets economic research. With a strong emphasis on employee growth, Bloomberg provides opportunities to engage in high-priority projects and collaborate with leading economists and analysts. The company fosters a culture of diversity and inclusion, ensuring that every voice is valued while equipping employees with the tools and resources needed to excel in their careers.
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 best projects related to data science and machine learning. This is your chance to demonstrate how you can turn complex data into actionable insights.
✨Tip Number 3
Practice makes perfect! Brush up on your Python and machine learning skills before the interview. You might get asked to solve a problem on the spot, so being sharp will help you stand out.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you’re genuinely interested in joining the Bloomberg team.
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 highlight your experience in quantitative analysis and machine learning. 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 economic research and how your background makes you a perfect fit for our team. Keep it engaging and personal – we love to see your personality come through.
Showcase Your Technical Skills:Since this role involves a lot of data work, make sure to highlight your Python skills and any experience with machine learning libraries. If you've worked with unstructured data or built models, let us know – we’re keen to hear about it!
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way to ensure your application gets into the right hands. Plus, it shows us you’re serious about joining our team at Bloomberg!
How to prepare for a job interview at Bloomberg L.P.
✨Know Your Data Inside Out
Before the interview, dive deep into the datasets you might be working with. Familiarise yourself with economic indicators, market trends, and any recent geopolitical events that could impact your analysis. This will not only show your passion for the role but also help you engage in meaningful discussions.
✨Showcase Your Python Skills
Prepare to demonstrate your Python expertise during the interview. Bring examples of past projects where you've built data pipelines or machine learning models. Be ready to discuss the libraries you used, like scikit-learn or PyTorch, and how they contributed to your project's success.
✨Communicate Clearly and Confidently
Strong communication skills are key for this role. Practice explaining complex concepts in simple terms, especially when discussing model evaluations or trade-offs. This will help you connect with your interviewers and showcase your ability to collaborate effectively with colleagues.
✨Stay Updated on Industry Trends
Keep an eye on the latest developments in machine learning and narrative economics. Being able to discuss current trends or breakthroughs in the field can set you apart from other candidates. It shows that you're not just qualified, but also genuinely interested in the industry.