Senior Data Scientist - London

Descartes Underwriting
London
1 month ago
Applications closed

Related Jobs

View all jobs

Senior Data Scientist – Machine Learning -  Defence –Eligible for SC

Senior Data Scientist

Senior Data Scientist

Senior Data Scientist

Senior Data Scientist (Document Search)

Senior Data Scientist

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 6 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

Descartes Underwriting is seeking aSenior Data Scientistto join ourUnderwriting Teambased inLondon.

Reporting to the Underwriting Manager, you will be a key contributor to the development of climate models or forecasting tools in close and effective cooperation with all business units.


Your responsibilities will include :


Individual contribution in Underwriting projects

  • Improve and develop new algorithms, new risk models and products for our B2B client;
  • Conduct structuring work, risk analysis and insurance proposal for worldwide public sector and corporate clients;
  • Collaborate with the business team and brokers to understand client needs and risk transfer challenges to successfully underwrite new business and renew accounts;
  • Operate in the London market, leading discussions and projects with brokers and partners.


Technical & Business Leadership

  • Be a referent for junior Underwriting Data Scientists and provide them guidance on technical modeling matters & business requirements;
  • Participate in the development of Descartes’ technological platform to differentiate Descartes from its competitors (nat cat models and pricing tools);
  • Collaborate with various divisions of Descartes technical teams (R&D Modellers, Data & Innovation team, Risk Management).



ABOUT YOU

EXPERIENCE & QUALIFICATIONS

  • Graduated from a Business or Engineering school/academic institutions with a specialization in data science, computer science, applied mathematics, climate and meteorological studies or related;
  • 4 years’ of significant experience minimum (post graduation) in data science or related;
  • Proven track record of significant experience in leading a (small) team and managing business projects;
  • Prior experience in structuring, pricing & underwriting (parametric) insurance covers for climate risks is a plus.

SKILLS

  • Proficiency in Python (e.g. pandas, scikit-learn);
  • Proficiency in statistics, probabilities, applied mathematics and machine learning methods;
  • Eye for quality, autonomous and attention to detail;
  • Fluency in English (written and verbal communication) is required;
  • Good command of one additional language (e.g. Chinese, French, Italian, German, Spanish...) is valued.

MINDSET

  • Interested in insurance industry and emerging risks modeling (climate);
  • 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 acquire responsibility;
  • Results oriented with the ability to work in a fast-paced and multi-cultural 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.


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: Technical online test
  • Step 3: In person or remote technical interview
  • Step 4: In person team interview to meet our team and discover our offices

Get the latest insights and jobs direct. Sign up for our newsletter.

By subscribing you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Portfolio Projects That Get You Hired for Data Science Jobs (With Real GitHub Examples)

Data science is at the forefront of innovation, enabling organisations to turn vast amounts of data into actionable insights. Whether it’s building predictive models, performing exploratory analyses, or designing end-to-end machine learning solutions, data scientists are in high demand across every sector. But how can you stand out in a crowded job market? Alongside a solid CV, a well-curated data science portfolio often makes the difference between getting an interview and getting overlooked. In this comprehensive guide, we’ll explore: Why a data science portfolio is essential for job seekers. Selecting projects that align with your target data science roles. Real GitHub examples showcasing best practices. Actionable project ideas you can build right now. Best ways to present your projects and ensure recruiters can find them easily. By the end, you’ll be equipped to craft a compelling portfolio that proves your skills in a tangible way. And when you’re ready for your next career move, remember to upload your CV on DataScience-Jobs.co.uk so that your newly showcased work can be discovered by employers looking for exactly what you have to offer.

Data Science Job Interview Warm‑Up: 30 Real Coding & System‑Design Questions

Data science has become one of the most sought‑after fields in technology, leveraging mathematics, statistics, machine learning, and programming to derive valuable insights from data. Organisations across every sector—finance, healthcare, retail, government—rely on data scientists to build predictive models, understand patterns, and shape strategy with data‑driven decisions. If you’re gearing up for a data science interview, expect a well‑rounded evaluation. Beyond statistics and algorithms, many roles also require data wrangling, visualisation, software engineering, and communication skills. Interviewers want to see if you can slice and dice messy datasets, design experiments, and scale ML models to production. In this guide, we’ll explore 30 real coding & system‑design questions commonly posed in data science interviews. You’ll find challenges ranging from algorithmic coding and statistical puzzle‑solving to the architectural side of building data science platforms in real‑world settings. By practising with these questions, you’ll gain the confidence and clarity needed to stand out among competitive candidates. And if you’re actively seeking data science opportunities in the UK, be sure to visit www.datascience-jobs.co.uk. It’s a comprehensive hub featuring junior, mid‑level, and senior data science vacancies—spanning start‑ups to FTSE 100 companies. Let’s dive into what you need to know.

Negotiating Your Data Science Job Offer: Equity, Bonuses & Perks Explained

Data science has rapidly evolved from a niche specialty to a cornerstone of strategic decision-making in virtually every industry—from finance and healthcare to retail, entertainment, and AI research. As a mid‑senior data scientist, you’re not just running predictive models or generating dashboards; you’re shaping business strategy, product innovation, and customer experiences. This level of influence is why employers are increasingly offering compensation packages that go beyond a baseline salary. Yet, many professionals still tend to focus almost exclusively on base pay when negotiating a new role. This can be a costly oversight. Companies vying for data science talent—especially in the UK, where demand often outstrips supply—routinely offer equity, bonuses, flexible work options, and professional development funds in addition to salary. Recognising these opportunities and effectively negotiating them can have a substantial impact on your total earnings and long-term career satisfaction. This guide explores every facet of negotiating a data science job offer—from understanding equity structures and bonus schemes to weighing crucial perks like remote work and ongoing skill development. By the end, you’ll be well-equipped to secure a holistic package aligned with your market value, your life goals, and the tremendous impact you bring to any organisation.