Data Engineer - Scientific Engine Airflow DVC - CDI

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 realtime monitoring from satellite imagery & IoT our stateoftheart 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 and launched Descartes Insurance a full stack insurer licensed to underwrite risk by the French Regulator (ACPR). With a growing corporate client base (350 and counting) our diverse team is headquartered in Paris and operates out of our 13 global offices in North America Europe Australia Singapore Hong Kong and Japan.

ABOUT YOUR ROLE

Due to our consistent growth we are expanding our Data Software and DevOps team. We are seeking profiles dedicated to data engineering. At the core of the development of our scientific engine modeling climate phenomena your main missions will be to create improve and maintain the data pipelines used to train our model and infer the different scenario to make a climate risk assessment. You will have to take initiative and assess the viability of proof of concept projects.

You will have to work with data scientists and software engineers to run and develop our models. You will be working along DevOps engineers to reliably put models in production and selected the compute/store instance needed to perform these tasks. Your secondary mission will be to automate the flow of information between the tech and business to monitor climate events.

KEY MISSIONS

• Setup automate maintain and update:
• Connections to external and internal APIs
• Data preparation process
• Model training and inference process
• Data storage process
• Associated CI/CD pipelines
• Associated package versioning and releasing pipeline
• Modularization of code base
• Notification tools to inform the team of the status of the operations

• Setup data storage data processing and data visualizing tools by :
• Assessing the pains and needs of the teams
• Benchmarking the open source and private solutions
• Assessing the security price and reliability of data architecture

• Following the development the evolution of technologies on the topic
• Forecasting the usage of the tools
• Tracking the cost of the tools

• Participate in:

• Tech stack selection
• Discussions with tech partners
• Training of software and underwriting teams
• Support and debug of internal users
  

TECH STACK

• Cloud provider: GCP
• Code versioning tool: Git Gitlab
• OS: Linux
• Container: Docker
• Container orchestrator: Kubernetes
• Website architecture: LAMP
• Code base: Python
• Notification tool: Slack
  

DATA STACK

• Types: images timeseries
• Storage: GCP bucket
• Version: DVC (roll out in progress)
• Pipeline: Airflow (PoC stage)
• Data base: to be setup depending on the use cases

In our project data is collected by sensors (satellite weather station IoT). We dont work with personal or sensitive data in most cases the data is publicly available (earthquake magnitude cyclone track precipitation ).

EQUIPMENT

• Laptop: Dell Latitude 7530
• OS: you decide
  
  

ABOUT YOU

EXPERIENCE & QUALIFICATIONS

Hard skills

• Knowledge of the tech stack or equivalent tools
• Experience converting python code to efficient data engineering tools (eg: spark)
• Experience with Docker
• Experience with a cloud provider (GCP AWS or azure)
• Experience automating a CI/CD pipeline
• Good knowledge in English and fluency in French

Soft skills

• Desire to train junior developers and explain CI/CD and cloud tools
• Desire to suggest improvements to the architecture

Nicetohave

• Experience working data science project or scientific code
• Experience with Kubernetes
• Experience in HPC
• Contribution to an open source project
  

MINDSET

• Strong interest with climate issue (its not a hoax many people suffer from it)
• Being comfortable to work alongside corporate insurers (some still wear suits )
• You enjoy CI/CD automation (or at least appreciate the elegance of a wellcrafted pipeline)
• Strong team spirit and ability to work (youll have to review code and have your code reviewed)
• Rigorous creative and meticulous mind (we handle large insurance we take our time)
• Strong desire to learn (theres no limitation to the tech used were happy to test and learn new tools)
• Eagerness to work in a multicultural environment (policies and teams are from all around the world )
  
  

WHY JOIN DESCARTES UNDERWRITING

• Join a company with a true purpose help us help our clients be more resilient towards climate risks;
• A competitive salary bonus and benefits (Premium Alan health insurance Swile restaurant vouchers Navigo reimbursement etc.);
• The opportunity to grow in your role as the company does;
• Commitment from Descartes to its staff of continued learning and development (think annual seminars training etc.);
• Be part of a collaborative diverse team where your ideas are heard;
• A paid referral scheme for successfully referring peers;
• Frequent team events.

OUR COMMUNITY

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.

HOW TO APPLY

If you want to develop your skills and work in a friendly startup atmosphere dont hesitate and send us your application!

If you dont check all the requirements in the description dont worry. We can try to make some room for you within the company if youre motivated to work on climate risk.

RECRUITMENT PROCESS

• Step 1: Call and HR Interview with our Talent Recruiter
• Step 2: Technical project submitted via GitHub
• Step 3: Technical interview
• Step 4: Manager interview
• Step 5: Final round interview with the team
  (Candidates can opt to have the manager interview before the technical project and interview)