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- Tasks: Analyse climate finance data and develop robust data pipelines using Python.
- Company: Join CPI, a leader in sustainable finance and climate policy analysis.
- Benefits: Enjoy hybrid working, competitive salary, and a range of benefits.
- Why this job: Make a real impact on global climate initiatives while advancing your data skills.
- Qualifications: Degree in a quantitative field or relevant experience; strong Python skills required.
- Other info: Flexible working patterns and a commitment to diversity and inclusion.
The predicted salary is between 39000 - 45000 £ per year.
Location: London
Reports to: Senior Data Analyst
Contract: Permanent, Full Time
Salary Range: £39,000 - £45,000 per annum (depending on experience)
About CPI
CPI is an analysis and advisory organization with deep expertise in finance and policy. Our mission is to help governments, businesses, and financial institutions drive economic growth while addressing climate change. CPI has six offices around the world in Austria, Brazil, India, Indonesia, South Africa, the United Kingdom, and the United States. CPI is known as a leader in tracking sustainable investment trends, identifying innovative business models, and supporting the solutions that can drive the transition to a low‑carbon, climate‑resilient, inclusive economy.
About the role
We are seeking an experienced and dedicated Data Analyst to join the Data Science Team within CPI. The successful candidate will work across the organisation, with a focus on CPI’s Tracking workstream. As part of our Tracking efforts, CPI produces the biennial Global Landscape of Climate Finance, the most comprehensive dataset and analysis of global climate financing available, used extensively in the Intergovernmental Panel on Climate Change (IPCC) Assessment Reports. The successful candidate will contribute to the creation and analysis of this dataset. Additionally, they will support the expansion of CPI’s Net Zero Finance Tracker, providing the most robust, comprehensive and transparent data on the financial sector’s transition to net zero, informing policy direction, investment strategy, and advocacy decisions. The analyst would also support the wider implementation of data science processes across the organization.
Key Responsibilities
- Support the research team in the efficient collection and analysis of varied and cross‑disciplinary data to incorporate into usable and reportable formats. This will include but is not limited to investment data and transaction and impact attributes.
- Develop robust data pipelines for the ingestion of these data sources.
- Develop scripts in Python to query, analyse, and interpret data using statistical techniques.
- Develop Python web scraping scripts to expand the data sources available for analysis.
- Provide input into reports and presentations to disseminate analytical outputs.
- Work with CPI’s communications and research teams to develop data visualisations and web interfaces.
- Contribute to expanding CPI’s AWS Cloud Platform, developing pipelines using AWS Glue and AWS Lambda.
Person Specification
Essential
- A commitment to CPI’s mission and values.
- Degree in a quantitative field, such as computer science, quantitative finance or economics, physics, engineering, mathematics, statistics, or data science. Candidates without such a degree but who can demonstrate experience in a similar Data Analyst / Data Scientist / Data Engineering role are welcome to apply. Non‑traditional qualifications with a significant Python for Data Analysis component will also be considered.
- Excellent Python skills for data processing and analysis (Jupyter notebooks, Pandas, Numpy) or experience with languages such as R with a willingness to translate those skills into Python.
- Strong record of data analytics work and development of robust data processing pipelines.
- Previous professional work experience in a similar role/related field.
- Fluency in written and spoken English.
- Ability to present complex data concepts to non‑expert colleagues.
- Highly organised, with the ability to manage workload and plan outputs.
Desirable
- Experience in web scraping using Python libraries (Scrapy / BeautifulSoup / Selenium etc.).
- Experience with data visualisation tools such as Tableau, or Python visualisation libraries such as matplotlib or seaborn.
- Familiarity with Bloomberg Terminal and BQuant.
- Experience with key energy and financial databases e.g., BloombergNEF, Refinitiv Eikon, Capital IQ, Rystad etc.
- Understanding of public and/or private international climate finance.
- Experience in Natural Language Processing, particularly data extraction.
- Experience using cloud‑based tools for data storage and processing (Azure, AWS, Google Cloud).
- Familiarity with Git workflow.
- Experience using AI Assistants such as Claude Code, Cursor, or Codex.
- Previous background and experience in finance and/or climate policy sectors.
Hybrid Working & Benefits
CPI UK have adopted a hybrid working approach, with many of our colleagues spending part of their working hours at home and part in the office, depending on the nature of the role they are in. We’re flexible on how this works and it may continue to change and evolve. Typically, we request that teams spend at least 40% of their time in the office with their colleagues. We’re also happy to discuss a range of flexible working patterns to meet your individual personal circumstances. We offer a range of competitive benefits as a CPI team member.
To Apply
Please submit your CV and respond to our application questions by Tuesday 7th April 2026. We may close applications early if we receive a strong number of candidates, so we’d recommend applying early to avoid missing out.
TIMELINE
- Application deadline: Tuesday 7th of April.
- Application review: by Thursday 9th of April
- UK interviews: 15th and 16th of April
Due to the importance of this role to our CPI projects we are looking to appoint quickly and will be reviewing applications as they are submitted, therefore interested candidates are advised to submit your application at the earliest convenience. We reserve the right to remove this advert, dependent on the level of response received.
Climate Policy Initiative is an equal opportunity employer and committed to improving diversity, equity, and inclusion within our organization. We work hard to create and maintain a supportive and inclusive environment where all individuals can maximise their full potential. Our CPI teams reflect a variety of backgrounds, talents, perspectives, and experiences. Our strong commitment to a diversity and inclusion is evident through our focus on attracting and retaining staff based on skills and merit. We welcome and strongly encourage applications from candidates of all identities and backgrounds, and do not discriminate on the basis of race, colour, religion, gender or gender identity, sexual orientation, national origin, disability, or age. We are committed to providing reasonable accommodations to applicants and colleagues with disabilities.
Data Analyst in London employer: CLIMATE POLICY INITIATIVE
Contact Detail:
CLIMATE POLICY INITIATIVE Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Analyst in London
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend events, and connect on LinkedIn. You never know who might have the inside scoop on job openings or can put in a good word for you.
✨Tip Number 2
Prepare for interviews by practising common data analyst questions. Get comfortable with explaining your past projects and how you've used Python for data analysis. The more you rehearse, the more confident you'll feel!
✨Tip Number 3
Show off your skills! Create a portfolio showcasing your data visualisations and projects. This is a great way to demonstrate your expertise and make a lasting impression on potential employers.
✨Tip Number 4
Don't forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, we love seeing candidates who are genuinely interested in joining our mission at CPI.
We think you need these skills to ace Data Analyst in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Data Analyst role. Highlight relevant experience and skills, especially in Python and data analysis. We want to see how your background aligns with our mission at CPI!
Answer Application Questions Thoughtfully: Take your time with the application questions. This is your chance to showcase your passion for climate finance and data analytics. We’re keen to understand your thought process and how you can contribute to our team.
Showcase Your Technical Skills: Don’t hold back on your technical skills! Whether it’s Python, data visualisation tools, or cloud platforms, let us know what you’ve got. We love seeing candidates who are confident in their abilities.
Apply Early!: We might close applications early if we get a strong response, so don’t wait until the last minute. Head over to our website and submit your application as soon as you can. We can’t wait to hear from you!
How to prepare for a job interview at CLIMATE POLICY INITIATIVE
✨Know Your Data Tools
Make sure you brush up on your Python skills, especially with libraries like Pandas and NumPy. Be ready to discuss how you've used these tools in past projects, as CPI is looking for someone who can hit the ground running with data processing and analysis.
✨Understand CPI's Mission
Familiarise yourself with CPI’s focus on climate finance and policy. Show genuine interest in their mission during the interview, and be prepared to discuss how your background aligns with their goals. This will demonstrate that you're not just looking for any job, but that you truly want to contribute to their cause.
✨Prepare for Technical Questions
Expect technical questions related to data analytics and pipeline development. Brush up on your knowledge of AWS services like Glue and Lambda, and be ready to explain how you would approach building robust data pipelines. Practising coding problems can also help you feel more confident.
✨Showcase Your Communication Skills
Since you'll need to present complex data concepts to non-experts, practice explaining your past projects in simple terms. Think about how you can convey your analytical outputs effectively, perhaps even preparing a mini-presentation or visualisation to share during the interview.