Data Analyst

Heidi's data lives on the growth side more than most companies' data does. Every week, signups become clinicians, clinicians become retained sessions, and retained sessions become the revenue that lets us build the next feature. We need someone who can sit inside that pipeline and tell us, honestly, whether it's working. You'll spend most of your time embedded with Growth and Marketing, but you'll go wherever the business needs eyes on a number. This month that might be campaign performance and channel mix, next month it's unpacking how user behaviour shows up in revenue retention. You've done this enough times to know how to structure the analysis, find the metric that actually matters, and bring people along without losing them in the SQL.

Responsibilities

Own the data models and analysis behind Growth and Marketing: campaign performance, channel mix, funnel conversion and acquisition metrics, end to end; Defend our CAC and budget guardrails with a commercial eye on every campaign; Take ambiguous questions from anywhere in the business and shape them into a clear analysis plan with insights people can act on; Build the dashboards and reports that let teams find their own answers, no analyst required; Turn findings into recommendations people can actually act on, and say no when a request is solving the wrong problem; Maintain the data pipeline end to end, from ingestion to the models built on top of it, so it runs clean and fast; Lead the 'why did this number move' investigations, and know the difference between a real trend and a broken pipeline; Work daily in dbt, Databricks and Omni, and help raise the bar for how data gets modelled and trusted here

Requirements

2-4 years of analyst experience with solid exposure to marketing or growth data in tech or SaaS, though we care more about what you've shipped/built than years on the clock; A romantic streak about software. You believe great products can transform someone's day; You go find the answer yourself before you ask someone to pull it for you; When a number looks wrong, your instinct is to dig in and find the root cause, not caveat it away; Passion for AI, shown through hands-on building, prototyping, or side projects; You default to building over requesting; You're confident in your thinking and open to being wrong. Great ideas win regardless of who surfaces them; Can you take a vague 'is this campaign working?' and come back with actionable insights?; Do you go find the answer yourself before asking someone to pull it for you?; When a number looks wrong, is your instinct to dig in and find the root cause rather than caveat it away?; Can you hold your own in a room with opinionated stakeholders and get them aligned on what the data actually says?

Benefits

$1,000 annual learning and development budget; $150/month health and wellness allowance; $500 home office budget; 26 weeks paid primary parental leave; 18 weeks paid secondary parental leave; fertility support up to $10,000; four weeks of work from anywhere per year; serious equity