Data Scientist

• Design relational, dimensional, and analytical data models from large, disparate datasets across the product ecosystem.
• Build, train, validate, and deploy machine learning models in production using MLOps practices.
• Develop data layers, views, and infrastructure to power reports and dashboards for aggregate and per-customer insights.
• Collaborate with data engineers and Salesforce architects to ensure pipeline integrity and data federation.

This role empowers small and mid-sized nonprofits to increase their social impact through data-driven automation and AI, enabling them to connect with people, build trust, and make good happen every day.

• 4+ years of hands-on experience in data science or data engineering with a track record of deploying ML models in production.
• Proficiency in Python and associated libraries for data manipulation and ETL/ELT processes.
• Advanced SQL proficiency and deep understanding of data warehousing, dimensional modeling, and schema design.
• Experience with cloud ML platforms (AWS SageMaker preferred) and automated deployment workflows.

Fully remote environment, collaborative culture, opportunity to work on greenfield AI/ML projects for the social good sector. Salary not specified.