Data Scientist

• Design relational, dimensional, and analytical data models from large, disparate datasets across the product ecosystem, extending them into Salesforce Data 360 for downstream analytics and AI agents.
• Partner with data engineers and Salesforce architects to define data requirements, ensure pipeline integrity, design schemas, and operationalize data flows, including zero-copy data federation between Snowflake/AWS and CRM systems.
• Build, train, validate, and deploy machine learning models in production, with emphasis on MLOps and monitoring.
• Transform complex model outputs into production-ready data products and structured data views, and communicate architecture decisions to technical and non-technical stakeholders.

This role enables nonprofits to leverage data-driven automation and AI, significantly increasing their social impact by streamlining operations and providing actionable insights.

• 4+ years of hands-on experience in data science or data engineering, with a proven track record of developing data models and deploying ML infrastructure in production.
• Proficiency in Python and associated libraries for data manipulation, ETL/ELT, and system integration.
• Hands-on experience with cloud ML platforms (AWS SageMaker preferred) and automated deployment workflows.
• Advanced SQL proficiency, deep understanding of data warehousing concepts, dimensional modeling (e.g., Kimball), schema design, and database design patterns for ML pipelines.
• Bachelor's degree in a technical field (Computer Science, Software Engineering, Information Systems, or related).

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