Data Scientist - Machine Learning
Climate change is creating a crisis for the insurance industry and those who rely on it for financial security.
Every year, severe weather causes billions of dollars of damage. Yet traditional insurers lack the tools to accurately assess and price severe weather risk. Without knowing what to expect, insurers expect the worst, leading to unaffordable premiums. For industries such as retail automotive and agriculture, traditional insurance is becoming unattainable. These business owners are at risk of financial devastation whenever a storm strikes.
Understory is the first company to solve the insurance coverage crisis with parametric insurance for severe weather, starting with hail. Our growing network of ground-based Dot weather sensors, combined with our Atmospheric Intelligence AI, allow us to assess and price any weather risk in the world.
When severe weather strikes, Understory detects it and triggers a fast, predetermined payout. There are no burdensome financial deductibles, and no lengthy claims process. Ultimately, Understory allows capital to quickly flow where it’s needed most after a disaster, protecting everything from automobiles to the world’s food supply.
An Understory Data Scientist assists in the analysis of weather station and air quality sensor data to improve our understanding of weather and air quality. They work closely with engineers and software developers to advance pattern detection algorithms, data analysis, prototyping systems, and large-scale applications that help produce interesting and meaningful weather products for our customers.
Your main role responsibilities will include:
- Build production-ready models using data from Understory’s networks
- Leverage brand new data to advance our understanding of severe weather and its impacts on people and property
- Incorporate new findings with current weather models to improve them
- Translate client and business needs into actionable analytical plans
- Work with our frontend team to explore the usefulness and usability of high-density data
You're exactly what we're looking for if you:
- Master’s in mathematics, computer science, finance, economics, or science-related field
- 1+ years of experience in commercial machine learning and data analysis
- Experience in algorithm development with Python, Matlab, R, regression analysis, cohort analysis, clustering, predictive models, and machine learning
- Experience with information retrieval and text analysis fundamental
- Familiarity working with UNIX-based systems
- Comfortable in a fast-paced and dynamic professional environment
- Independent with the ability to work well as part of a team
- Base salary commensurate with experience
- Full-time benefits