Data Scientist

Data Scientist, Analytics

(Remote, Canada)

Events in recent years have made us all too familiar with the havoc that natural disasters can wreak, and the increasing frequency and intensity with which they are occurring. Despite record levels of losses, conventional methods of risk modeling continue to paint at best an incomplete picture of these threats.

ZestyAI uses novel data gathering and data science methods to produce higher quality information about the risks to property from catastrophes like storms and wildfires. While AI alone may not be able to thwart these disasters, it can help us become more prepared for them, and ultimately that will lead to better outcomes.

As a Data Scientist, Analytics, you will work closely with product, engineering, and machine learning teams to apply data science to complex product and business problems.You will use diverse data sources to evaluate product performance, generate actionable insights, and support evidence-based decision-making across ZestyAI’s products.You will also help establish the analytical processes, monitoring frameworks, and best practices needed to maintain product quality and scale the organization. You thrive in a collaborative, creative environment that moves fast and are comfortable implementing structures and processes to help the company scale.

The Opportunity:

• Translate product management, engineering, and business questions into structured analytical approaches, applying appropriate statistical, experimental, and data science methods to measure product performance and guide decision-making
• Champion data quality of ZestyAI data products
• Lead product monitoring and quality assurance by designing and maintaining dashboards and KPIs
• Develop automated ETL and data workflows
• Iterate rapidly on everything; all of the above happens in a fast-paced business-driven environment that you must be comfortable with

What You Bring to the ZestyAI Team:

• BA / BS degree in Math, Physics, Engineering, Computer Science, or Economics

• MS or Ph.D. is certainly a bonus

• 2–3 years of experience in analytics, data science, or related roles, including experience building data workflows, defining metrics, and developing dashboards or monitoring tools

• Strong organizational and management skills with past experiences implementing best practices and processes