Data Scientist

CREA (Centre for Research on Energy and Clean Air) are looking for a Data Scientist with strong scientific skills to join their data team.

Overview:

• Full-time, freelance contract
• Language: English
• Location: Anywhere (Remote)
• Salary: not applicable
• Applications closing: until filled

Job Description

CREA (Centre for Research on Energy and Clean Air) is a not-for-profit organization committed to tackling global air pollution through data-driven research and analysis. Our mission is to identify the causes, impacts, and solutions for air pollution, providing scientific support to policymakers, corporations, and advocacy groups worldwide to drive clean energy transitions and improve public health.

Responsibilities

As a Data Scientist at CREA, you will:

• Collaborate with regional teams on air quality and health impact analyses
• Automate and produce regular briefings compiling air quality, industrial, and economic datasets
• Correct energy and air quality data for weather conditions
• Implement or refactor epidemiological models to assess health impacts
• Visualise pollutant dispersion and trends effectively
• Compute air pollution exposure maps using regression or machine learning models
• Conduct detailed geospatial statistics from satellite or atmospheric modelling datasets
• Maintain and improve our data infrastructure, including scrapers and pipelines
• Provide technical support to organisation members

Depending on your background and expertise, your role may also involve:

• Writing explanatory analyses of air pollution episodes in various cities
• Building CO2 emission estimates using trade and energy balance data

Role Requirements

We seek candidates who demonstrate:

• High proficiency in R, Python, and Git
• Experience with geospatial and environmental data
• Ability to build and communicate elegant data visualizations
• A proactive, solution-oriented approach and a commitment to learning

Nice-to-have skills include:

• Background in atmospheric chemistry, energy science, or epidemiology
• Knowledge of software engineering best practices and DevOps tools
• Familiarity with Postgres/PostGIS, Docker, and cloud-based infrastructure
• Communication skills for co-writing scientific reports and collaborating with analysts

How to apply?

To apply for this role, please fill in the application form.

Duration of the application process is indicative and may be adjusted:

• Application form (20 min)
• Technical task #1 (40 min)
• Short interview with the team lead (20 min)
• Technical task #2 (4 hours)
• Conversation with the data team (1 hour)
• Cultural fit interview (30 min)
• Final interview with the team lead and director (30 min)

If you don’t feel you meet every single requirement but are passionate about our mission and believe you could contribute to our team, we encourage you to apply nonetheless. We value diverse perspectives and skills, and you may be the perfect fit in ways we haven’t imagined yet.