Senior Data Scientist

Job not on LinkedIn

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🇺🇸 United States – Remote

💵 $150k - $165k / year

⏰ Full Time

🟠 Senior

📊 Data Scientist

👻 Ghost score 0%

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LEMNIS

WebsiteLinkedInAll Job Openings

11 - 50 employees

🤲 Charity

📚 Education

🌍 Social Impact

Charity • Education • Social Impact

LEMNIS is a public charity dedicated to expanding learning opportunities for young people by creating inclusive, community-connected learning environments. The organization partners with researchers and practitioners in neuroscience, social science, digital technology, and artificial intelligence to design experiences that foster belonging, connection, and lifelong growth. Lemnis works alongside changemakers and operates divisions such as Mainstay and InsideTrack to scale its impact; it is based in Beaverton, Oregon and notes it does not accept unsolicited grant proposals.

📋 Description

• 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

🎯 Requirements

• 5+ years building predictive models that someone actually used • Several years owning predictive modeling problems, including calibration, threshold-setting, and detecting feature leakage • Practical NLP experience, including text classification, clustering, embeddings, or similar applied work • Strong SQL skills • Working Python skills for modeling and analysis • Solid applied statistics • Experience with a modern cloud warehouse such as Snowflake, BigQuery, Databricks, or similar • Experience with in-warehouse AI or agent tooling • Excellent written and verbal communication • Comfort with ambiguity and honesty about uncertainty • Experience working in version control with code review • Experience productionizing model output into an operational workflow • Experience scheduling and monitoring recurring production jobs • Track record of prioritizing ambiguous business goals into scoped projects • Willingness to evaluate model performance across student populations and document limitations • Nice to have: dbt or similar transformation tooling, dimensional modeling, or analytics engineering exposure • Nice to have: AI evaluations or prompt evaluation familiarity • Nice to have: Sigma, Looker, Hex, Tableau, or similar BI tool experience • Nice to have: Experience working closely with analytics or data engineers • Nice to have: Linguistics or computational linguistics background • Nice to have: EdTech, higher education, or student success background

🏖️ Benefits

• Collaborative and inclusive work environment • Personal and professional growth opportunities • Promotion-from-within opportunities • Support and mentorship aimed at long-term success • Primarily remote work arrangement