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Founding Engagement Analyst

2 days ago

Calgary, Alberta, Canada OpenHouse Full time

| CAD $90K–$120K + Bonus | North America (Hybrid)About the Role

is hiring an Engagement Analyst to join our client engagement team and work directly with home builders on high-stakes pricing, demand, and growth decisions.

This role sits at the intersection of client decision-making, analytics, and product signal. You'll partner closely with Engagement Managers to structure ambiguous questions, design and execute analysis, and translate insights into clear options and recommendations that executives actually act on.

Your work will directly shape pricing, incentive, and growth decisions made by executive leadership teams.

Unlike traditional analytics or customer success roles, Engagement Analysts are expected to be in the room participating in client meetings, presenting exhibits, and building judgment by seeing how recommendations are debated and implemented in the real world.

You'll often be working with incomplete data, imperfect signals, and time-constrained decisions, clarity under uncertainty matters more than perfect answers.

This is a foundational hire. High performers develop deep context across clients and the platform and can grow into engagement leadership, product management, or front-deployed roles over time.

About

is the leading AI research and deployment company transforming the $300B+ new home construction industry.

Our Quantitative AI platform is deployed across 30+ markets in the U.S. and Canada, helping forward-thinking builders make smarter decisions around pricing, demand, forecasting, and growth. Our vision is to become the operational intelligence backbone for the homebuilding ecosystem.

What You'll DoStructure & Scope Decisions

  • 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

Analyze to Inform Action

  • 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

Build Decision-Ready Outputs

  • 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

Be Close to the Client

  • 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

Leverage the Platform

  • 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

How We Measure Success

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

Methods You'll Use (and Learn)

  • 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.

Who This Role Is For

This role is ideal for someone early in their career who is excited by:

  • Working directly with clients and owning decisions that materially impact their business
  • Structuring ambiguous problems and turning analysis into action
  • Applying analytics to pricing, demand, and growth decisions
  • Learning fast in environments without playbooks
  • Building judgment at the intersection of data, strategy, and product

You don't need to have done everything before but you should be eager to take real responsibility and grow quickly.

What You'll Bring

  • 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.)

Bonus Points

  • 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.

First 90 Days: What Success Looks Like30 Days

  • Understand the OpenHouse platform, data model, and engagement workflow
  • Shadow client meetings and identify recurring decision patterns
  • Contribute analysis included in client-facing exhibits
  • Proactively surface an initial data inconsistency or assumption risk

60 Days

  • Own an analytical workstream tied to a live client decision
  • Present portions of analysis directly to clients
  • Proactively surface insights without being asked

90 Days

  • Deliver a full, end-to-end analysis that directly informs a client decision
  • Be recognized by at least one client as meaningfully improving decision-making
  • Contribute insights that influence product or deployment priorities
  • Progression is driven by judgment, client trust, and decision impact, not tenure.

Compensation & Benefits

  • CAD $90,000–$120,000 base salary + bonus (post-probation)
  • Medical & dental benefits (post-probation)
  • 15 days paid time off