At a Glance
- Tasks: Transform mobile data into vital statistics for health and humanitarian efforts.
- Company: Join Flowminder, a non-profit making a real difference globally.
- Benefits: Permanent role with hybrid work options and opportunities for travel.
- Other info: Be part of a small, dynamic team with a mission to help vulnerable communities.
- Why this job: Your work can directly impact lives and shape critical decisions.
- Qualifications: Strong quantitative skills, Python expertise, and professional French required.
The predicted salary is between 81000 - 99000 £ per year.
About the role
This week CNN and Reuters reported on our work in DRC together with Vodacom, WHO, Congo government, African CDC and others where we are using mobile-phone data to understand population movements and get ahead of the Ebola outbreak. This is part of Flowminder's work, and we need one more person on the team doing it.
You'll turn mobile operator, survey and spatial data into population and mobility statistics that ministries of health, national statistics offices and UN agencies rely on for outbreak response, humanitarian planning and development decision-making in DRC and beyond. About a third of the role is training and building capacity with our partner institutions, in French and English, including travel to the countries we work in. It's a job where what you produce on a Tuesday can shape decisions on the ground by Friday.
We're looking for someone with a strong quantitative background, solid Python and time-series skills, spatial data experience, and professional working French.
Permanent, full-time, based in Stockholm or Southampton (hybrid). Deadline: 30 September 2026. We review on a rolling basis.
About Flowminder
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.
Data Analyst / Data Scientist (French speaking) in Portsmouth employer: Flowminder
Flowminder is an exceptional employer dedicated to making a meaningful impact on vulnerable populations through data analysis and capacity building. With a flexible working culture, opportunities for professional growth, and the chance to travel to diverse countries like the Democratic Republic of the Congo and Senegal, employees can engage in rewarding work that directly influences public health and disaster management. The collaborative environment fosters innovation and allows team members to develop their skills while contributing to significant global challenges.
StudySmarter Expert Advice🤫
We think this is how you could land Data Analyst / Data Scientist (French speaking) in Portsmouth
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We think you need these skills to ace Data Analyst / Data Scientist (French speaking) in Portsmouth
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at Flowminder, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Flowminder. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Flowminder
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Flowminder!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
