Data Analyst / Data Scientist (French speaking)

About Us

Flowminder is a non-profit foundation. We enable decision makers to access the data they need to transform the lives of vulnerable people, at scale.

We analyse pseudonymised mobile operator data, satellite imagery and household survey data to measure where people are and how they move. Flowminder researchers were the first to use mobile operator data to track population movements after a large-scale disaster and during a major infectious disease outbreak, following the 2010 Haiti earthquake and cholera outbreak. We work with national statistics offices, health ministries and disaster management agencies in low- and middle-income countries, alongside UN agencies, the World Bank and development banks.

We are a small team, based mainly in Southampton and Stockholm, working in countries including the Democratic Republic of the Congo, Haiti, Ghana and Pakistan. Our working language is English, but much of our work with partners is in French.

Why this role, and why now

Flowminder's data has been central to the Ebola response in eastern DRC. Mobile operator data gives near real-time estimates of population movement and connectivity. That supports decision-makers managing disease spread — for example, where to place surveillance sites.

The work is operational and time-pressured. We aim to provide the best data possible for the context and the time available. The limits that come with those constraints must be communicated clearly alongside the data.

We are focused on delivering that impact across Africa, where most of our partners work in French.

Once the data is produced, we support its use. We run webinars, deliver training and strengthen capacity, so the data feeds into decisions and policy.

The role

About two thirds is analysis. You will work with geo-referenced time series derived from mobile operator data, alongside survey and spatial data, to produce statistics on population mobility. 

About one third is training and capacity strengthening. You will help partner staff in national statistics offices, UN agencies, health ministries and disaster management agencies understand mobile phone data, use our products, and eventually run analyses themselves. Much of this is delivered in French, in person and remotely. Travel to Africa and other regions is expected as part of the role. 

We are looking for someone who is both strong analyst and a strong communicator.

Analysis

• Exploratory and standard analysis of time series, geo-referenced time series, maps and geo-referenced survey data.
• Producing standard mobility reports and indicators, and interpreting what they show.
• Anomaly detection and data cleaning, including spotting artefacts caused by network changes rather than real movement.
• Combining sources: mobile operator data, survey data, spatial data.
• Assessing and quantifying the limits and uncertainty of what we publish, and running quality checks before release.
• Developing and improving analysis methods, and supporting the engineering team to put them into operational pipelines.
• Protecting the privacy of data subjects and working in line with GDPR.

Training and capacity strengthening

• Designing and delivering training on mobile phone data and on Flowminder’s products, in French and English, for partners of varying technical background.
• Producing training material, guidance notes and documentation that people can use after you have left the room.
• Supporting partners between sessions as they apply what they have learned to their own questions.
• Gathering what you learn from partners and feeding it back into how our products are designed.
• Travelling to partner countries where a project needs it, for example the Democratic Republic of the Congo, Senegal or Côte d’Ivoire.  

Communication

• Choosing how to present findings to suit the audience, whether that is a ministry, a donor, a mobile operator or a colleague.
• Building clear data visualisations and maps.
• Stating the limits of the data plainly, including when the honest answer is that the data cannot say.
• Presenting at workshops and conferences, and reporting internally to technical and non-technical colleagues.

About You

You must already have the right to work in the UK or Sweden.

Your motivation should come from an interest in these problems:

• How to extract better information from mobile phone usage data.
• How to tell normal movement from a genuine anomaly.
• How to present graphs, maps and insights so that people who are not analysts can act on them.
• How to build lasting analytical capacity in the countries where we work, rather than delivering reports indefinitely.

Essential

• A genuine wish to see your work improve the lives of vulnerable people.
• Professional working proficiency in French, written and spoken, good enough to run a technical training session and answer questions on your feet.
• Excellent written and spoken English.
• A Master's or PhD in a quantitative discipline, or equivalent applied experience. Statistics, mathematics, informatics, demography, geography, epidemiology, econometrics and physics are all relevant.
• Strong quantitative reasoning under uncertainty, combining analytical thinking with contextual knowledge.
• Demonstrable experience analysing time series collected outside controlled conditions, including sparse and irregular data.
• Experience with spatial and geo-referenced data.
• Python for analysis, and code that others can read, run and maintain.
• Experience with data visualisation and mapping.
• Experience explaining technical work to non-technical audiences, whether through training, teaching, facilitation or user support.
• Sound judgement on privacy (Working in line with GDPR is crucial).
• Willingness to travel to partner countries, typically for short visits. Likely destinations include the Democratic Republic of the Congo, Senegal and Côte d’Ivoire.

Desirable

• Experience designing or delivering training or capacity strengthening for government or partner staff.
• Human mobility, migration or flow statistics; demography, public health, epidemiology or disaster management.
• Applied work in low- and middle-income countries, or sustained time spent in them.
• Experience of mobile operator data or call detail records.
• SQL, geographic information systems, machine learning, or privacy-preserving methods for aggregate data.
• Confident, critical use of AI assistants for coding, analysis and documentation, including judging when their output is wrong.
• Experience developing and managing data-driven projects.

Other organisations might call this role Data Analyst, Data Scientist, Insights Analyst, Statistician, Analyst-Trainer, or Technical Adviser. Our focus is operational impact rather than publication.