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- Tasks: Help build country-risk indicators and develop visualisation tools using large datasets.
- Company: Bloomberg is a global leader in economic and political analysis, with a strong team of economists and reporters.
- Benefits: Enjoy a diverse and inclusive work environment with opportunities for collaboration and growth.
- Why this job: Make an impact by contributing to vital economic research while enhancing your data analysis skills.
- Qualifications: Experience with Python, data analysis, and collaboration on projects; recent graduates are encouraged to apply.
- Other info: This is a 12-month contract role based in London.
The predicted salary is between 36000 - 60000 £ per year.
Bloomberg has an outstanding capacity to explain the economic and political landscape globally, supported by nearly 50 economists and 200 reporters worldwide. Bloomberg Economics offers comprehensive macroeconomic research for Terminal subscribers, including detailed forecasts and thematic research. We are seeking a data analyst to help build country-risk indicators for a 12-month period.
The role: The successful candidate will contribute to developing country risk indices.
Responsibilities:
- Build country-level risk indices using large datasets, collaborating with Bloomberg Economics colleagues.
- Develop solutions to keep indices current via APIs and automated scripts.
- Create visualization tools to display indices.
- Collaborate with the Geoeconomics team to publish analysis featuring these indices on the Bloomberg Terminal.
Qualifications:
- Experience with Python for analyzing large datasets, calling APIs, and visualizing data.
- Experience collaborating on data projects using Git.
- Knowledge of software engineering best practices (maintainable/scalable code, testing, code review).
- Proficiency in English.
- Academic or professional experience applying statistical and econometric methods to data analysis.
- Experience applying quantitative methods to political science, environmental science, or economics topics.
Preferred:
- Degree in political science or economics.
- Experience automating scripts with Apache Airflow.
- Knowledge of other programming languages, especially R.
- Recent graduates with relevant project experience are encouraged to apply.
Next steps: If interested, please apply to be notified of the next steps. Bloomberg offers a diverse, inclusive, and collaborative work environment that inspires employees to excel.
Bloomberg Economics - Country Risk Data Analyst (12 Months Contract) | London, UK employer: Bloomberg
Contact Detail:
Bloomberg Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Bloomberg Economics - Country Risk Data Analyst (12 Months Contract) | London, UK
✨Tip Number 1
Familiarise yourself with Bloomberg's products and services, especially their economic research. Understanding how they operate will help you tailor your conversations during interviews and demonstrate your genuine interest in the role.
✨Tip Number 2
Brush up on your Python skills, particularly in data analysis and visualisation. Consider working on personal projects or contributing to open-source projects that showcase your ability to handle large datasets and create visual tools.
✨Tip Number 3
Network with current or former employees of Bloomberg, especially those in similar roles. They can provide valuable insights into the company culture and expectations, which can be beneficial during your application process.
✨Tip Number 4
Stay updated on global economic trends and political developments. Being knowledgeable about current events will not only help you in interviews but also show your passion for the field and your readiness to contribute to Bloomberg Economics.
We think you need these skills to ace Bloomberg Economics - Country Risk Data Analyst (12 Months Contract) | London, UK
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience with Python, data analysis, and any projects involving country risk indices. Use specific examples to demonstrate your skills in handling large datasets and collaborating on data projects.
Craft a Strong Cover Letter: In your cover letter, express your enthusiasm for the role and how your background in political science or economics aligns with Bloomberg's mission. Mention your experience with APIs, automated scripts, and any tools you've used for data visualisation.
Showcase Technical Skills: Clearly outline your technical skills in your application. Include your proficiency in Python, Git, and any experience with Apache Airflow or R. Highlight any relevant coursework or projects that demonstrate your ability to apply statistical methods.
Demonstrate Collaboration Experience: Since the role involves collaboration with various teams, provide examples of past experiences where you worked effectively in a team setting. This could include group projects during your studies or previous job roles.
How to prepare for a job interview at Bloomberg
✨Showcase Your Technical Skills
Make sure to highlight your experience with Python, especially in analysing large datasets and calling APIs. Be prepared to discuss specific projects where you've used these skills, as this will demonstrate your capability to build country-level risk indices.
✨Demonstrate Collaboration Experience
Since the role involves working closely with colleagues and teams, share examples of past collaborations on data projects. Mention your experience using Git, as it shows you understand version control and teamwork in coding environments.
✨Discuss Your Understanding of Economic Indicators
Be ready to talk about your knowledge of economic and political landscapes, particularly how they relate to country risk. This could involve discussing any relevant academic or professional experiences that apply statistical and econometric methods to data analysis.
✨Prepare for Problem-Solving Questions
Expect questions that assess your ability to develop solutions for keeping indices current. Think of examples where you've automated processes or created visualisation tools, and be ready to explain your thought process and the impact of your solutions.
