The lab is based at the African Climate and Development Initiative at the University of Cape Town.
The Climate Risk Lab is looking to recruit recent PhD, MSc, or first-class Honours graduates with backgrounds in data science, machine learning, computer science, mathematics, statistics, econometrics, engineering, physics or related fields.
The Climate Risk Lab’s mission is to create breakthrough science, tools, and policies to protect people and nature from climate change.
Projects underway in the lab include building models to understand past impacts and predict future impacts from climate change on people and nature, as well as AI-enhanced synthesis of evidence about what works for climate solutions for human health and wellbeing.
About the Fellowship
The goal of the Data Science and Machine Learning Fellowship is to accelerate the capacity of the lab to deliver breakthrough science using the latest tools while strengthening the research and data science skills of successful candidates.
The role entails providing data science support to an interdisciplinary team of research staff, projects and other activities within the Climate Risk Lab, working largely with climate, environmental, health, and socioeconomic data.
Fellows will also be encouraged to lead on a project that is meaningful to them.
Fellows will be paired with a senior data scientist or postdoctoral researcher to provide mentorship support during their position.
They will also have the opportunity to lead data-intensive research within the lab and participate in working group meetings with international collaborators and/or conferences.
This is a full-time, one-year fellowship with an opportunity for a one-year renewal based on candidate performance. There may also be potential for the Fellowship to be turned into a PhD scholarship or Postdoc funding.
Fellows will be based in Cape Town at the Climate Risk Lab.
Job Summary
- Employer: The Climate Risk Lab
- Job Type: Full-time
- Location: Harare, Zimbabwe
- Category: Data Science
- Salary: The remuneration range for this role will be competitive with academic and market rates and based on candidate experience.
- Closing Date: 2026-10-05
Key Responsibilities
- Analysis of big climate, environmental, health, and/or socioeconomic datasets.
- Developing and applying AI tools to enhance data science workflows and supporting other analysts to use AI tools.
- Downloading, cleaning, processing, and optimising large datasets.
- Mainstreaming best practices for reproducible workflows, including contributing to and maintaining Git repositories.
- Development and maintenance of code to improve the efficiency of processing and analysing large spatial-temporal datasets, including parallel computing approaches.
- Documenting and communicating workflows.
- Leading or co-leading a research project towards a peer-reviewed publication, toolkit, or dataset.
- Availability to travel internationally if needed.
Requirements
- An MSc degree or first-class Honours degree, completed or in the final year, in data science, machine learning, computer science, mathematics, statistics, or related fields.
- Proficiency in programming languages, preferably Python or R.
- Solid grounding in statistics and/or data science principles.
- Excellent oral and written communication skills.
Salary
The remuneration range for this role will be competitive with academic and market rates and based on candidate experience.
How to Apply
Frequently Asked Questions
What qualifications or education do I need to apply for a Data Science and Machine Learning Fellowship in Zimbabwe?
Most fellowships require a bachelor's degree in computer science, statistics, mathematics, or a related field. Practical experience with Python, R, or SQL and familiarity with machine learning libraries like scikit-learn or TensorFlow is highly valued. Some programs may accept candidates with strong portfolios from bootcamps or self-taught backgrounds.
What would my day-to-day responsibilities look like in this fellowship?
You will typically clean and analyze climate-related datasets, build predictive models, and present findings to stakeholders. Expect to collaborate with researchers, attend team meetings, and document your code and methodologies. Some fieldwork or engagement with local communities may be required depending on the project focus.
How does work culture in Zimbabwean research or NGO settings typically operate?
Workplaces often emphasize respect for hierarchy and formal communication, especially in established institutions. Punctuality is expected, though flexibility may exist in remote or hybrid arrangements. Building personal relationships and networking are important for career advancement in the local context.
What career progression can I expect after completing this fellowship?
Fellows often transition into full-time data scientist roles, climate policy advisory positions, or pursue advanced degrees. Experience with climate risk modeling is increasingly sought by international NGOs, government ministries, and regional organizations. Some fellows establish consulting practices serving agricultural or insurance sectors.
What benefits are typically included in fellowship positions in Zimbabwe?
Benefits vary by employer but may include medical aid contributions, limited annual leave, and professional development allowances. Pension schemes are less common in fellowship roles compared to permanent positions. Always clarify contract terms, as some fellowships are stipend-based without full employment benefits.
How should I apply, and what do Zimbabwean employers in this field prioritize?
Submit a tailored CV highlighting relevant projects and a cover letter demonstrating your interest in climate applications. Employers prioritize demonstrated problem-solving skills, GitHub portfolios, and understanding of local challenges like drought or flood prediction. Networking through local tech communities and LinkedIn can significantly improve your visibility to hiring managers.
