LEMNIS

Data Scientist

• Find and ship predictive signals across student engagement, outcomes, and partner health
• Build predictive models that integrate with partners’ existing systems and drive action
• Set actionable alert thresholds and account for false-positive costs
• Evaluate model performance across student populations and document limitations
• Monitor deployed models for drift and retire models that no longer provide value
• Decide when an analysis, definition change, or conversation is preferable to building a model
• Own scheduling and monitoring for models using maintainable orchestration
• Apply embeddings, clustering, and classification to conversational, support, service, and other unstructured data
• Turn unstructured-data findings into product and partner-experience improvements
• Build text-analysis foundations for retrieval and AI tooling
• Own in-warehouse AI configuration, verified queries, prompts, agent tooling, and semantic views exposing model output
• Build and maintain an AI evaluation framework with precise rubrics, sampling methodology, and improvement reporting
• Set evaluation standards and share methodology with Product and Engineering
• Equip internal teams with reusable data and analysis for strategic partners
• Build tooling and training that enable teams to answer questions independently
• Document reasoning, assumptions, and tradeoffs in the internal data knowledge base
• Work in dbt/code alongside engineers and contribute to shared definitions
• Collaborate with Senior Data Engineer, Senior Analytics Engineer, Product, Engineering, Partner Success, Leadership, and external stakeholders

Senior Data Scientist