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Dwelly is building an AI operating system for residential lettings across the UK and Ireland. The company operates 15,000+ properties with $470M GMV and has raised $263M from top-tier investors. You will be the first dedicated data scientist in the newly launched Growth function, owning the analytical agenda alongside commercial and product leadership.
This is a thought-partner role where you bring hypotheses, challenge priorities, and build analyses that drive decisions—not a service seat. You'll work with an exceptional data asset: years of conversations with landlords and tenants, complete property management records, payment histories, and call recordings. With LLMs now making unstructured data usable, you can answer questions no other proptech company in the market can.
Key responsibilities include: building churn early-warning systems that identify root causes (e.g., service failures vs. property sales) and quantify impact; expanding share-of-wallet by estimating landlords' off-platform portfolios and mining call data for product insights; analyzing pricing elasticity across acquired agencies and optimizing rent review prioritization; underwriting Rent Guarantee products using proprietary loss data; designing statistically rigorous growth experiments with holdout groups and uplift estimates; and owning the Growth data layer (pipelines, metrics tree, LLM eval harnesses).
You'll need 5+ years as a data analyst or scientist with full-stack capability: Python, SQL, dbt-style pipeline building. Statistical depth is essential—experiment design, causal inference (diff-in-diff, matching, synthetic control), survival analysis, elasticity estimation. You apply pragmatic ML (churn propensity, uplift modeling, pricing, forecasting) and prefer production-ready logistic regression to notebook gradient boosting. Fluency with LLMs on messy text and audio, plus ability to build eval sets, is required. You're autonomous, customer-centric, and thrive in fast-paced startups.
