At a Glance
- Tasks: Develop climate models and innovative algorithms to manage corporate risks.
- Company: Join Descartes, a leading corporate insurance group at the forefront of AI and data analysis.
- Benefits: Enjoy competitive salary, bonuses, remote work options, and continuous learning opportunities.
- Other info: Be part of a diverse, dynamic team committed to innovation and excellence.
- Why this job: Make a real impact in climate resilience while working with top talent from prestigious institutions.
- Qualifications: Master’s student in relevant fields with experience in data science or climate modelling preferred.
The predicted salary is between 50000 - 70000 £ per year.
Building Resilience in a World at Risk. Descartes is a corporate insurance group for worldwide companies and institutions. Descartes was born from a conviction that the growing complexity of corporate and climate risks demands a new approach to insurance. At the forefront of AI and Data analysis, Descartes utilises cutting-edge technology combined with a new generation of data sources, to model, assess and manage risks. Since 2019, Descartes has secured a leading position in parametric (re)insurance combining scientific & technological expertise with a new approach.
Our highly diverse and specialized team of 250+ people includes the largest modelling team in the industry featuring tech and modeling innovators, scientists in physics and climatology, as well as insurance veterans and underwriters. Due to rapid growth, we are seeking to expand our Data Science team across our Underwriting functions and we are looking for Data Scientists 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:
- Improving or developing new algorithms, new risk models and products for our B2B clients;
- Identifying, implementing and deploying new statistical and machine learning methods to differentiate Descartes from its competitors;
Requirements:
- Master’s student in data science, computer science, applied mathematics, statistics or meteorological studies or related;
- Ideally a previous experience (long-term internship) in data science or climate modeling is valued;
- 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) is required;
- Good command of one additional language (e.g. Chinese, French, Italian, German, Spanish...);
- Excellent team player with an entrepreneurial mindset and value of diversity;
- Results oriented, high energy, with the ability to work in a dynamic and multi-cultural environment;
- Eager to learn more about the insurance industry.
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.); Be part of a dynamic 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 punctual home office days.
At Descartes Underwriting, we cherish the value of diversity whatever it may be. With equal skills, all our positions are open to people with disabilities.
Step 1: HR Interview with our Talent Recruiter
Step 2: Technical online test on Github
Step 3: Remote technical interview with a Data Scientist
Step 4: In-person team interview to meet our Data Scientist team and discover our offices (could be held remotely if you are abroad).
Data Scientist (Machine Learning) employer: Descartes Underwriting
Descartes is an exceptional employer, offering a unique opportunity for Data Scientists to contribute to innovative climate models and risk assessment tools in the heart of London. With a commitment to employee growth through continuous learning and development, a dynamic international team, and a strong focus on diversity, Descartes fosters a collaborative work culture that empowers individuals to thrive while making a meaningful impact in the insurance industry. Enjoy competitive salaries, bonuses, and the flexibility of home office days as you join a company dedicated to building resilience against climate risks.
StudySmarter Expert Advice🤫
We think this is how you could land Data Scientist (Machine Learning)
✨Embrace Online Competitions
Get involved in online data science competitions like Kaggle or DrivenData. These platforms not only let you showcase your skills but also help you build a portfolio that stands out to hiring companies like Descartes Underwriting when you're aiming for that entry-level role.
✨Join Data Science Meetups
Look for local data science meetups or workshops happening in your area. These are perfect for connecting with industry professionals and fellow newbies, giving us the chance to learn the ropes and get our foot in the door at companies like Descartes Underwriting.
✨Networking Through University Career Services
Don't forget to leverage your university's career services! They often have exclusive internships and networking events specifically for entry-level data science positions. This is a golden opportunity to meet recruiters from companies like Descartes Underwriting.
✨Spotlight Your Skills Online
Create a strong online presence by sharing your projects and insights on platforms like GitHub or LinkedIn. Make sure to apply directly through Descartes Underwriting’s career page, where your unique skills can shine in their entry-level data science openings!
We think you need these skills to ace Data Scientist (Machine Learning)
Some tips for your application 🫡
Show Off Your Data Skills:As you're aiming for an entry-level data science role at Descartes Underwriting, don't forget to highlight your proficiency in programming languages like Python or R. Dive into your CV and mention any relevant projects or coursework that demonstrate your data analysis skills or machine learning knowledge.
Include Relevant Projects:If you've done any data-related projects, whether in your studies or during a personal quest, showcase them in a portfolio. This gives us a tangible sense of your capabilities and shows your hands-on experience with data manipulation, visualisation, or model building.
Tailor Your Cover Letter:When crafting your cover letter, make sure to express your enthusiasm for data science and how this role at Descartes Underwriting aligns with your career goals. Consider sharing why you’re drawn to data-driven decision-making and how you see yourself growing in this field.
Show Your Curiosity:In the data science world, curiosity is key! Mention any online courses or certifications you've pursued that complement your studies. This could be anything from a statistics certification to a data visualisation workshop. It shows us you're serious about learning and growing in this field.
How to prepare for a job interview at Descartes Underwriting
✨Brush Up on Your Statistics
For a data science role, the interview may involve some statistical questions or problems. Make sure you're comfortable with concepts like probability, distributions, and hypothesis testing. This will not only help you answer questions but also show your analytical thinking.
✨Get Hands-On with Tools
Familiarise yourself with popular data science tools like Python, R, and SQL. If you're asked about specific projects, be ready to discuss the tools you used and how they contributed to your analysis. Showing that you not only know the theory but can apply it is essential!
✨Showcase Relevant Projects
As an entry-level candidate, your portfolio is crucial. Bring along examples of data projects you've worked on, whether during your studies or personal projects. Discuss the challenges you faced and how you overcame them, highlighting your problem-solving skills.
✨Prepare for Case Studies
Entry-level interviews in data science often include case studies where you'll have to analyse a dataset or solve a problem on the spot. Try out some practice case studies beforehand, so you're not caught off guard. It's all about displaying your thought process and how you tackle data-driven challenges!
