ABOUT DESCARTES UNDERWRITING
Descartes was born out of the conviction that the ever-increasing complexity of risks faced by corporations, governments and vulnerable communities calls for a renewed approach in insurance. Our team brings together industry veterans from the most renowned institutions (AXA, SCOR, Swiss Re, Marsh, Aon, ...) and scientists on top of their field to bring underwriting excellence. After 5 years of existence, Descartes has secured a leading position in parametric insurance for weather and climate-related risks utilizing machine learning, real-time monitoring from satellite imagery & IoT. After a successful Series B raise of $120M USD, we launched Descartes Insurance, a 'full stack' insurer licensed to underwrite risk by the French regulator ACPR. With a growing corporate client base (400+ and counting), our diverse team is headquartered in Paris and operates out of our 17 global offices in North America, Europe, Australia, Singapore, Hong Kong and Japan. Descartes is trusted by a panel of A-rated (re)insurers to carry out its activities.
ABOUT YOUR ROLE
Due to rapid growth, we are seeking to expand our Data Science team across our
Underwriting
functions and we are looking for a
Data Scientist
to join our team in
London .
As a Data scientist, your missions will focus on making direct contributions to the development of new climate models or forecasting tools.
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;
Working autonomously and pragmatically to make appropriate technical decisions.
ABOUT YOU
EXPERIENCE & QUALIFICATIONS
Master’s student in computer science, applied mathematics, statistics or meteorological studies;
Ideally a previous experience (long-term internship) in data science or climate modeling.
SKILLS
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...) is valued.
MINDSET
Interested in weather and natural perils modeling (wildfires, hail, tsunamis, earthquakes etc);
Strong team spirit and ability to work under pressure;
Highly motivated, able to meet deadlines set;
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;
Eagerness to work in an international environment.
WHY JOIN DESCARTES UNDERWRITING ?
Opportunity to work and learn with teams from the most prestigious schools and research labs in the world, 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 ;
Join a company with a true purpose – help us help our clients be more resilient towards climate risks;
A competitive salary, bonus and benefits;
You can benefit from a punctual home office days.
At Descartes Underwriting, we cherish value of diversity whatever it may be. 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.
RECRUITMENT PROCESS
Step 1: HR Interview with our Talent Recruiter
Step 2: Online technical project
Step 3: Remote Technical interview
Step 4: In person final round interview with the team
