CareerVillage.org

Data Scientist

• Design, build, and deploy predictive models that improve learner outcomes and product performance, including user behavior prediction, recommendations, ranking, and classification
• Develop, own, and continuously improve end-to-end data science workflows, including ongoing model iteration, retraining, and performance monitoring over time
• Take ownership of existing and new predictive models, diagnosing performance issues, adapting to data or product changes, and iterating to improve real-world impact over time
• Partner closely with product, engineering, research, and leadership to translate ambiguous questions into data science solutions
• Work closely with engineering partners to ship, maintain, and iterate on models in production; you will not be expected to build production infrastructure alone
• Contribute to AI and model evaluation frameworks, including offline metrics, experimentation, and qualitative analysis
• Analyze large, complex datasets to identify patterns, opportunities, and risks across our platforms
• Communicate modeling approaches, assumptions, tradeoffs, and results clearly to technical and non-technical stakeholders
• Write technical documentation, reports, and presentations that drive product and organizational decisions
• Support responsible, ethical, and equitable use of data and AI in education-focused products

Account Executive

• Own top deals: Lead discovery, demo, negotiation, and contracting for high-value partnerships that anchor our GTM strategy.
• Build and manage the pipeline: Oversee outreach, qualification, and forecasting. Maintain strong Salesforce discipline and ensure consistent visibility into performance metrics, with a focus on growing the number of active partner deployments and learners using Coach through those partners.
• Spearhead the sales motion: Set weekly cadences, coach on discovery and objection handling, and model commercial excellence through hands-on selling.
• Integrate AI and automation: Leverage AI to improve productivity, accelerate research, and test new approaches to prospecting and engagement.
• Run rapid market experiments: testing segments, messaging, target profiles, and partnership models, then codify what works into clear, repeatable playbooks that reveal where the strongest traction exists.
• Collaborate cross-functionally: Partner with Product, Engineering, and Impact teams to feed insights from the field back into the roadmap, messaging, and evidence-building.
• Measure and optimize performance: Track conversion, cycle time, CAC, ROI, and scale metrics such as partners launched and active learners per deployment. Use data to guide resourcing and prioritize opportunities.
• Drive GTM strategy: Help define market segmentation, ICPs, pricing logic, and value propositions across key buyer segments (job training, higher ed, corporate L&D). You’ll help decide where we bet next (by segment) and design experiments to prove or disprove those bets.
• Guide/Develop assets: Partner with Impact and Marketing to create early case studies, ROI models, and success narratives that drive credibility and scale.

Data Scientist

Founding Account Executive