FAQs
What is the main purpose of the Data Analyst role at CDP?
The main purpose of the Data Analyst role at CDP is to use data to help companies, investors, and governments build a thriving economy that works for people and the planet, by enhancing data integration and augmentation capabilities, and developing impactful data products.
What qualifications are required for the Data Analyst position?
Candidates should have a strong ability to code in SQL, Python, PySpark, and Notebooks, with at least 2 years of applied experience in data analytics and/or data science, alongside proven experience in statistical modeling and machine learning techniques.
What technologies will I be using in this role?
The role will involve working with SQL, PySpark, Azure DevOps, and data visualization tools such as Power BI, among other technologies.
How many years of experience are required for this position?
A minimum of 2 years of applied experience in data analytics and/or data science is required for the Data Analyst position.
Is experience in environmental science beneficial?
Yes, domain expertise in fields related to environmental science, governance, or management is considered a big plus for this position.
Who will I be reporting to in this role?
You will be reporting to the Squad Lead of Data Augmentation & Modelling.
Where are the CDP offices located for this position?
The position is based at either the CDP office in London or the CDP office in Berlin.
What kind of benefits does the Data Analyst role offer?
The role offers a salary between £40,000 - £47,000 per annum, 30 days of holiday plus bank holidays, generous non-contributory pension provision, Employee Assistance Programme, life assurance, training and development opportunities, and flexible working options.
Is prior experience with Azure necessary?
While not strictly necessary, experience with cloud computing in Azure or similar platforms is preferred for this position.
What types of statistical modeling will I be involved with?
You will be involved in regression, forecasting, and time-series analysis as part of the statistical modeling activities in this role.
