Application Guide
How to Apply for Consultancy in data science, predictive modelling, remote sensing, time series and methodological support for early warning systems
at Action Against Hunger
🏢 About Action Against Hunger
Action Against Hunger is a global humanitarian leader with over 40 years of experience saving lives through hunger prevention, nutrition, and water sanitation programs. Working with them means directly contributing to life-saving interventions in some of the world's most vulnerable regions, like the Sahel, where their anticipatory action projects help communities prepare for and mitigate food and pastoral crises.
About This Role
This remote consultancy is at the cutting edge of humanitarian innovation, focusing on strengthening the Pastoral Early Warning System (PEWS) in Senegal. You will develop experimental predictive models, analyze historical time series, and propose alert thresholds to enable anticipatory action, directly impacting how humanitarian organizations respond to food and pastoral crises in the Sahel.
💡 A Day in the Life
A typical day might involve cleaning and analyzing historical time series data from various sources, experimenting with different predictive models, and documenting your findings. You could also be in virtual meetings with PEWS stakeholders to discuss threshold definitions or to present preliminary results, all while working remotely and collaborating with a multidisciplinary team across time zones.
🚀 Application Tools
🎯 Who Action Against Hunger Is Looking For
- Advanced degree in data science, statistics, remote sensing, or a related field, with a strong portfolio of applied predictive modeling projects.
- Proven experience in time series analysis and forecasting, preferably in environmental or humanitarian contexts, using tools like Python (pandas, statsmodels, scikit-learn) or R.
- Familiarity with remote sensing data (e.g., NDVI, rainfall estimates) and their application to food security or pastoral early warning systems.
- Experience working in or with developing countries, ideally in the Sahel region, and understanding of the unique challenges of data-scarce environments.
- Strong communication skills to translate complex analyses into actionable recommendations for non-technical stakeholders.
📝 Tips for Applying to Action Against Hunger
Tailor your CV and cover letter to highlight specific projects where you developed predictive models or conducted time series analysis for early warning, food security, or related fields.
Demonstrate familiarity with the Sahel context by referencing relevant data sources (e.g., CHIRPS, MODIS) and challenges (e.g., pastoral mobility, climate variability) in your application.
Emphasize any experience with nowcasting or short-term forecasting, as this is a key component of the consultancy.
Showcase your ability to work remotely and collaborate with distributed teams, as the position is remote and likely involves coordination with colleagues in Senegal and other countries.
Include a portfolio or GitHub link showcasing code and analyses related to time series, predictive modeling, or remote sensing, if available.
✉️ What to Emphasize in Your Cover Letter
["Your technical expertise in predictive modeling and time series analysis, with concrete examples of models you've built and their impact.", 'Your understanding of early warning systems and how data science can enhance anticipatory action in humanitarian contexts.', 'Experience working with remote sensing data and integrating multiple data sources for analysis.', 'Your ability to communicate complex findings to non-technical audiences and provide actionable recommendations.']
Generate Cover Letter →🔍 Research Before Applying
To stand out, make sure you've researched:
- → Learn about Action Against Hunger's specific projects in Senegal and the Sahel, particularly the 'Strategic alliances for anticipatory action in response to food and pastoral crises in the Sahel' project.
- → Understand the Pastoral Early Warning System (PEWS) in Senegal: its objectives, data sources, and current analytical methods.
- → Research common predictive modeling techniques used in food security and early warning, such as seasonal forecasting, machine learning for crop yield prediction, and nowcasting.
- → Familiarize yourself with key remote sensing indices like NDVI, rainfall estimates (e.g., CHIRPS), and their limitations in pastoral contexts.
💬 Prepare for These Interview Topics
Based on this role, you may be asked about:
⚠️ Common Mistakes to Avoid
- Submitting a generic application that doesn't demonstrate specific interest or experience in humanitarian data science or early warning systems.
- Overemphasizing academic or theoretical knowledge without showing practical application in real-world, data-scarce settings.
- Neglecting to mention remote sensing or time series analysis, which are core requirements for this consultancy.
- Failing to tailor your application to the Sahel context, showing a lack of understanding of the region's unique challenges and data landscape.
📅 Application Timeline
⏰ Deadline: September 30, 2026
We recommend applying at least a few days early to avoid last-minute technical issues.
Typical hiring timeline:
Application Review
1-2 weeks
Initial Screening
Phone call or written assessment
Interviews
1-2 rounds, usually virtual
Offer
Congratulations!
Ready to Apply?
Good luck with your application to Action Against Hunger!