Senior Data Scientist

Key Responsibilities

• Design and deliver end-to-end predictive models (including partner churn prediction, lead scoring, and partner health scores), translating complex business questions into rigorous, production-ready analytical solutions.
• Develop and maintain attribution, marketing mix models and other marketing analytics frameworks that inform resource allocation and campaign strategy.
• Apply statistical methods to identify leading indicators, drivers, and patterns across partner data; communicate findings and trade-offs clearly to technical and non-technical stakeholders.
• Own the full ML lifecycle, from problem framing and feature engineering through model training, validation, deployment, and monitoring, ensuring models remain accurate, interpretable, and maintainable over time.
• Establish and uphold repeatable standards for model development, documentation, and validation that enable consistent, trustworthy DS/ML output across the team.
• Identify opportunities to apply ML and data science techniques to new business problems and proactively surface recommendations to leadership.
• Build and deploy agentic workflows and Claude Skills that automate analytical and modeling tasks, accelerate DS/ML development, and extend the team's capacity.
• Evaluate and recommend emerging AI tools and techniques relevant to data science and analytics.
• Act as an AI resource and mentor for the broader analytics team, modeling effective AI-assisted development practices and actively contributing to a shared culture of AI literacy.
• Partner closely with Sales, Marketing, and CX stakeholders to understand business context, identify and execute high-value analyses, and translate complex model outputs into clear, actionable insights and business narratives that directly shape organizational strategy and operations.
• Bring structure, documentation, and process discipline to ambiguous technical domains, ensuring work is reproducible and knowledge is shared.

Qualifications

• 6-8+ years of demonstrated on-the-job experience across the entire ML lifecycle, building and deploying in production the kinds of models this role requires: churn prediction, propensity/upsell scoring, health scores, lead scoring, media mix modeling, or closely analogous work.
• Strong quantitative foundation: proficiency in statistical modeling, experimental design, and analytical methods applied to real business problems.
• Highly proficient in SQL and Python for data manipulation, analysis, and modeling.
• Meaningful hands-on experience building agentic workflows, Claude Skills, or LLM-based automations using Claude, Cursor, or equivalent generative AI tools to accelerate analytical and ML workflows on the job.
• Familiarity with AI operational practices (prompt libraries, guardrails, output validation) that enable consistent and reliable AI-assisted work.
• A natural mentor and collaborator; a strong communicator who can explain complex technical concepts clearly to varied audiences.
• A self-starter who works independently, persists until the job is done, and stays calm and resourceful in a high-growth, startup-like environment.
• Passionate about our mission to teach kids to read.