Data Scientist

• Set up and maintain the data warehouse and related data infrastructure.
• Build and maintain dashboards and data visualisations for Customer Success, leadership, and other commercial stakeholders.
• Set up data pipelines and help establish a data warehouse, including connecting data from multiple sources that are not currently joined.
• Own SQL across the company, including writing, maintaining, and updating queries for reporting and analysis needs.
• Support some infrastructure and pipeline work with help from a backend engineer.
• Work with customer success and possibly product managers to inform decisions based on usage data and the product roadmap.
• Create analytics around feature adoption and engagement, including identifying which features drive retention and which are less used.

• Strong SQL and Python skills are required, with emphasis on fundamentals.
• Experience with BI or dashboarding tools such as Metabase, Looker, Tableau, Retool, or similar.
• Engineering experience with data warehouse setup and data pipeline work is important.
• Experience with SaaS, software platforms, finance, or other environments with complex usage data is preferred but not required.
• The person should be proactive, self-managing, and able to work semi-autonomously.
• Strong communication skills, with the ability to explain data clearly to non-technical commercial stakeholders.

Experience with SaaS, software platforms, finance, or other environments with complex usage data

• equity
• other benefits