Blue Marble Microinsurance (BMM) is a for-profit, social enterprise that aims to create markets for microinsurance by utilizing a new, mission-driven business model: collaborative innovation. BMM aims to narrow the global protection gap by designing and executing ventures enabling risk protection for the emerging middle class. BMM is owned by eight insurance companies collaborating to develop innovative solutions that protect the underserved.
About the Role
BMM is accelerating, piloting and scaling ventures in Africa, Asia and South America. The project is to join our data science team to lead the development of new parametric products, e.g. through applications of Machine Learning and Artificial Intelligence, as well as support in the design, pricing and tracking of existing parametric products across all ventures. BMM makes use of alternative climate and agriculture data sets to develop index products to protect smallholder farmers, example of such products include satellite-based weather index insurance.
Lead the development of new parametric products. This will include managing the process of developing a new product, as well as researching, programming, modelling, testing and documenting new products created
Support in the design, pricing and monitoring of existing parametric products across all BMM’s ventures
Qualifications and Skills
Bachelor’s Degree, Preferred Master’s Degree, in Statistics, Data Science or Climate Science
Two to five years of relevant experience
Expertise in R and preferred knowledge of Python
Project management and research skills
Proficient documenting skills with MS Word
Preferred knowledge of ML and AI applied to parametric products
Preferred knowledge of GIS applications (e.g. QGIS)
Preferred knowledge in the financial inclusion sector
Ability to structure and manage complex tasks
Resourcefulness and ability and drive to work independently
Ability to work in country of residency
How to Apply
Send your CV (PDF) to firstname.lastname@example.org with “Data Scientist” in the subject, tell us what you like about the role and why you believe you were made for the role. Please include one sample of your work with R and MS Word.