About the Data Scientist position

Good Tree is one of California's largest vertically integrated Cannabis delivery services. That means we work with data across the supply chain, and interact with over 100k customers. We work tirelessly to improve the customer experience while building a more inclusive Cannabis industry.

We are looking for a skilled Data Scientist who will help us analyze large amounts of raw information to find patterns and use them to optimize our performance. You will build data products to extract valuable business insights, analyze trends and help us make better decisions.

We expect you to be highly analytical with a knack for analysis, math, and statistics, and a passion for machine learning and research. Critical thinking and problem-solving skills are also required.

Data Scientist responsibilities are:

  • Research and detect valuable data sources and automate collection processes

  • Perform preprocessing of structured and unstructured data

  • Review large amounts of information to discover trends and patterns

  • Create predictive models and machine-learning algorithms

  • Modify and combine different models through ensemble modeling

  • Organize and present information using data visualization techniques

  • Develop and suggest solutions and strategies to business challenges

  • Work together with engineering and product development teams

You will get to work on a wide domain of problems including:

  • inventory optimization

  • staffing optimization

  • report automation

  • consumer surveys

  • customer segmentation

  • time-series analysis

  • geospatial analysis

Data Scientist requirements are:

  • 2+ years' experience of working on Data Scientist or Data Analyst position

  • Strong analytical skills, with business acumen

  • Strong communication and presentation skills

  • Good problem-solving abilities

  • BSc or BA degree in Computer Science, Engineering or another relevant area; graduate degree in Data Science or other quantitative field is preferred


Los Angeles or Bay Area preferred