Founding Engagement Analyst

OpenHouse.ai is an AI research and deployment company transforming the new home construction industry. They are seeking an Engagement Analyst to work with home builders on pricing, demand, and growth decisions, collaborating closely with Engagement Managers to provide actionable insights based on data analysis.

Responsibilities

• Partner with Engagement Managers to frame client problems using structured thinking (SCR / MECE)
• Define learning agendas, hypotheses, and analytical approaches tied to real business decisions
• Translate qualitative client context into clear data questions and modeling assumptions
• Use SQL and Excel to extract, clean, and join data from multiple sources
• Use Python notebooks (Pandas / NumPy) for exploratory analysis, forecasting, pricing, and scenario modeling
• Ensure analysis is reproducible, documented, and auditable end-to-end
• Convert analysis into one-message exhibits, sensitivity tables, and concise executive memos
• Clearly articulate observations → implications → trade-offs → recommendations
• Maintain assumptions and decision logs so recommendations are traceable and defensible
• Participate in client meetings and interviews to capture firsthand context
• Present portions of analysis directly to clients
• Learn how executives react to data, challenge assumptions, and make trade-offs
• Deeply engage with outputs from our Quantitative AI engine
• Build frameworks and scenarios that help clients understand what to do next
• Surface recurring client needs and feedback that inform product priorities
• Success is not defined by task completion. Your work succeeds when it: Leads to better decisions with measurable business outcomes, Builds long-term client trust and confidence, Improves how our product evolves in the real world
• Marketing & Growth Analytics: funnels, cohorts, retention, segmentation
• Forecasting & Revenue: time series, seasonality, scenario modeling
• Pricing & Monetization: elasticity, discount impact, willingness-to-pay
• Causal Inference: A/B testing, Difference-in-Differences, quasi-experiments
• Risk & Sensitivity: back-testing, error analysis, confidence intervals
• Method selection matters — you’ll be expected to explain •why• an approach fits the decision

Skills

• Strong analytical and structured problem-solving skills (SCR / MECE mindset)
• Comfort working with data and ambiguity
• Clear written and visual communication (pyramid-structured thinking)
• Technical fluency with SQL and Python
• Quantitative academic background (Economics, Statistics, Data Science, Engineering, Analytics, Finance, etc.)
• Experience creating executive-ready exhibits or decision memos
• Exposure to pricing, forecasting, or experimentation in a client context
• Consulting, analytics, product, or tech experience
• Familiarity with housing, construction, or real estate economics
• AI-native analyst mindset: actively using AI tools to accelerate analysis, stress-test reasoning, and improve clarity while maintaining full accountability for outputs
• Judgment matters more than tooling

Benefits

• Medical & dental benefits (post-probation)
• 15 days paid time off

Company Overview