What you will own in this role (accountability factors, collaboration/ownership breakdown, day to day tasks, high level projects)
As a founding member of the data science team, the data scientist will be an integral part of optimizing premium pricing, predicting tail risk triggers, and creating an automated price quoting engine. The data scientist:
- Will have two to five years of data science and/or machine learning experience
- Is excited about expanding use cases for existing models, making improvements to current models, and working closely with business to put models into production.
After some experience, the data scientist would be also involved in:
- Identifying new datasets,
- Researching optimal algorithms to reduce portfolio loss, and
- Deriving insights to improve products and customer experience.
As a fully remote organization, the candidate will need to be self-driven.
What experience we think is the right fit (skills, former jobs, past projects, specific knowledge to this position)
Core competencies:
- Hands-on experience with data-centric language (Python) not only to manipulate data and draw insights from diverse data sets but also to integrate models into production services.
- Hands-on experience in various Python libraries (Matplotlib, Numpy, Pandas, and Scikit-Learn) and Jupyter Notebook
- Knowledge and experience in statistical and data mining techniques, e.g., regression, clustering, classification
- Working cross-functionally to define problem statements, collect data, build analytical models, and drive solutions
- Ability to communicate data driven stories to technical- and non-technical audience
Preferred competencies:
- Hands on experience in Keras and SQL
- Familiarity with neural networks, natural language processing, recommender systems
- Domain knowledge in insurance, financial services, advertising, or marketing industry
