ABOUT DESCARTES UNDERWRITING
Descartes was born out of the conviction that climate change calls for a revolutionary approach in insurance to better protect corporations, governments, and vulnerable communities. We offer a new generation of parametric insurance that builds resilience against the full spectrum of climate and emerging risks. Utilizing Machine Learning and real-time monitoring from satellite imagery & IoT, our state-of-the-art climate tech provides innovative coverage for all trade sectors in all regions of the world. After a successful Series B raise of $120M USD, Descartes Underwriting is proud to be recognized among the French Tech Next40. With a growing corporate client base (150+ and counting) - our diverse team operates out of our global offices headquartered in Paris and based in Singapore, Sydney, New York, London, Madrid, Frankfurt and Hong Kong.
ABOUT YOUR ROLE
Due to rapid growth, we are seeking to expand our Underwriting team and we are looking for a Data Scientist. At the core of our company’s strategy, your missions will focus on making direct contributions to the development of new climate models of forecasting tools :
If you join the Underwriting team, your key missions will include :
- Improving or developing new algorithms, new risk models and products for our B2B client ;
- Identifying, implementing and deploying new statistical and machine learning methods to differentiate Descartes from its competitors ;
- Participating in the development of Descartes’ technological platform ;
- Collaborating with the business team to understand client needs and issues to further strengthen our technical excellence ;
- Taking on management responsibilities as both you and the company develop ;
- Participating in our R&D sessions ;
- Working autonomously and pragmatically to make appropriate technical decisions.
EXPERIENCE & QUALIFICATIONS
- Masters student in computer science, applied mathematics, statistics or meteorological studies ;
- Ideally a previous experience (long-term internship) in data science or climate modelling ;
- Proficient in statistics, applied mathematics and machine learning methods ;
- Capable of building high-performance algorithms ;
- Proficiency in Python (e.g. scikit-learn) ;
- Fluency in English (written and verbal communication) required ;
- Good command of one additional language (e.g. Chinese, French, Italian, German, Spanish…) valued.
- Interested in weather and natural perils modelling (cyclones, wildfires, hail, tsunamis, earthquakes etc) ;
- Strong team spirit and ability to work under pressure ;
- Eagerness to solve complex problems and technical challenges ;
- Rigorous, creative and meticulous mind ;
- Strong desire to learn and commitment to the organization’s mission ;
- Results oriented, high energy, with the ability to work in a dynamic and multi-cultural environment ;
- Motivated to help improving businesses’ and communities’ resilience to climate change.
WHY JOIN DESCARTES UNDERWRITING?
- Opportunity to work and learn with top data scientists from the most prestigious schools and research labs in France, allowing you to progress towards technical excellence ;
- Commitment from Descartes to its staff of continued learning and development (think annual seminars, training etc.) ;
- Work in a collaborative & professional environment ;
- Be part of an international team, passionate about diversity ;
- Benefit from a referral scheme for successfully referring peers ;
- You can benefit from a punctual home office days.
HOW TO APPLY ?
You may check off several but not necessarily all the expected boxes? Motivation and feeling are key elements for us!
If you want to develop your skills and work in a friendly startup atmosphere, don't hesitate and send us your application! https://www.descartesunderwriting.com/careers/
At Descartes Underwriting, we are committed to fighting against all forms of discrimination and for equal opportunities. We foster an inclusive work environment that respects all differences.
With equal skills, all our positions are open to people with disabilities.