Riskwolf is growing.
Our strategic interest is to build up a strong data team that scouts new sources for connectivity risks and turn them into priceable insurance products.
Partnering with the leadership team, you will test and develop next-generation, purely data-driven, insurance products (“parametric insurance”).
Your daily work includes hunting innovative and new data sources for Internet availability data, building statistical models for prediction of downtimes and outages and bring them to life on the Riskwolf platform.
- Identify new data sources that can be used for pricing and a better understanding of connectivity risks
- Be capable to efficiently solve business problems from a data perspective by choosing the right tools and methods (and challenge data and methods from 3rd parties)
- Engineer and analyse data (collection, cleansing, exploratory data analysis)
- Design and simulate parametric insurance products based on clear inputs
- Build statistical models and improve them (incl. Machine Learning techniques)
- Use state-of-the-art cloud computing to test and run the models
- Support the DevOps team to deploy pricing algorithms to the Riskwolf cloud platform
- Lay the foundation stone to grow the Riskwolf data team
- Growth and development potential raising employees market value. Learn from highly-skilled, productive and motivated people
- Attractive working environment allowing to combine creativity, self-management with a getting-it-done attitude
- Significant empowerment and flexibility in terms of working hours and time off
- Be part of a fast-growing, innovative, early stage InsurTech and participate in the upside
- Fair and equal team salary. Global hiring possible with service contract incl. social security costs.
- Personal budget for things where you think it creates to most value for you (e.g. for co-working, equipment, training, etc.)
Your skills and experiences
- Proactively take opportunities and address problems
- Able to work remote-first - Hands-on and no fear of new technics and tools
- See the glass half-full not half-empty
- Be able to communicate complex facts in a simple to understand language (in English)
- Self-motivated by complex challenges and large-scale data sets
- Experienced in predictive analytics and statistical modelling in R, Python and/or Matlab
- Basic understanding of the insurance domain (>1 years)
- Bonus-points: Trained as an actuary