Senior BI Analyst

We’re Real Work
, a team of builders and problem‑solvers based in Austin, Texas. Our mission is to help home service professionals earn the trust they deserve online.

Real Work is the marketing engine behind thousands of contractors nationwide. We transform their best jobs into SEO‑optimized stories, photos, and reviews that drive growth. Through integrations with leading field service platforms, we automate meaningful customer engagement after each job and use job content to help contractor’s online presence better reflect the quality of their work in the field.

Real Work is based 100% in the USA and headquartered in Austin, TX.

As a Senior BI Analyst at Real Work, you’ll be the analytical brain behind how our product gets better, how our customers get more value, and how the business makes smarter decisions. You’ll sit at the intersection of Product, Engineering, Customer Success, and the executive team, and your work will directly shape what we build, how we measure it, and how we know it’s working.

This is not a dashboards‑on‑demand role. What we need is someone who can look at the data, form a real point of view about what’s going on in the business, and then go build the analysis that proves or disproves it. You’ll be expected to ask better questions than the people asking you for reports, and to translate raw data into recommendations a CEO or product lead can act on tomorrow.

This is also an AI‑native role. We expect you to use modern AI tools as a core part of how you work every day: writing and debugging SQL, exploring datasets, drafting analyses, building dashboards, and pressure‑testing your own thinking. If your current workflow doesn’t already include AI as a daily collaborator, this isn’t the right role for you.

• Own product and customer analytics end-to-end; from the event model and data tables to the dashboards executives, product leaders, and CS managers actually use.
• Partner with Product and Engineering to instrument new features, define what success looks like before launch, and report back on whether we hit it.
• Dig into customer behavior to identify retention drivers, churn signals, and the engagement patterns that separate our best customers from the rest and translate those findings into product and CS recommendations.
• Build and maintain a set of executive and operational dashboards that tell the story of the business at a glance. Kill the ones that don’t.
• Design and analyze A/B tests for product changes, onboarding flows, and CS interventions, with clear hypotheses, sample sizes, and readouts.
• Use AI tools every day to move faster – generating SQL, exploring data, drafting analysis, and producing visualizations – and help us raise the bar for what an AI‑native analytics function looks like.
• Work cross‑functionally with Rev Ops, BI, Engineering, Product, and CS to make sure the data we trust is the same data everyone else sees.
• Bring strategic thinking to the table. We don’t want a ticket‑taker; we want someone who will tell us what we should be looking at next.

• Building a retention model that ties product engagement (job follow‑up call completion, review velocity, widget engagement, website performance) to renewal probability; and figuring out which levers actually move it.
• Taking over the event model and analytics for Real Work Websites and widgets: traffic, conversion, content engine performance, phone tracking, and the metrics that prove our sites win work for contractors.
• Running a controlled experiment on a new onboarding flow and writing the readout that tells the product team whether to ship, kill, or iterate.
• Producing a quarterly executive readout on the health of the customer base (segmented by product mix, customer demographics, and tenure) that the leadership team can actually make decisions from.
• Replacing a sprawling set of legacy dashboards with a tighter, more honest set of metrics that can be used to support the workflow of our individual contributors and decision making of our executive team.

• 4–6 years in a product, business, or data analytics role, ideally at a SaaS company. Comfortable owning analysis…