Growth Product Manager

Hybrid NYC ( 3 days a week in office)

$160k - $190k base + 10% bonus + equity

We are building the first AI visualization platform for aesthetic and wellness care, a place
where people can see a credible, achievable version of themselves before ever stepping into a
practice.

Out of our proprietary platform which powers 4,000+ practices, 2M+ users, and over
$3B in client revenue, we are now building the consumer side: the product that turns curiosity into
a booked consultation, and a booked consultation into a lifelong patient. You will be part of our
early startup team.

Mission
To own the scan-to-booking conversion engine for our product and make our partner practices
demonstrably more successful, measured by the rate at which consumers complete an AI
assessment and book a paid consultation with their local practice. This role exists because
practice retention depends on practice ROI, and practice ROI depends on one number moving
up and to the right: bookings per scan.

Success in this role means delivering the following within the first 12 months. These are the
metrics you will be evaluated against.
1. Lift scan-to-booking conversion rate by 30% within 12 months (baseline to be
established in week 2), through a continuous experimentation cadence of no fewer than
4 shipped A/B tests per month in GrowthBook.
2. Reduce scan abandonment by 20% within 9 months by instrumenting the full funnel,
identifying the top three drop-off points in the first 30 days, and shipping targeted
interventions against each.
3. Stand up and operate the products lifecycle program in Customer.io within the first
90 days, launching at minimum: a scan-abandonment recovery series, a post-scan
booking nurture, and a lapsed-user re-engagement flow. Target: recover 15% of
abandoned scans within 6 months of launch.
4. Build one compounding growth loop by month 6: referral, re-scan, or post-booking
that generates measurable second-order scans at a cost below paid acquisition
benchmarks.
5. Establish the practice-retention leading-indicator dashboard within the first 60
days, covering bookings per scan, time to first booking, consumer re-engagement rate,
and a churn-risk signal. Dashboard must be self-served by the product and CS teams
without analyst support.
6. Translate experimental learnings into the product roadmap quarterly. By end of Q2
in-seat, at least two shipped product features should trace directly back to insights from
your experiments.
Role Competencies
● SQL fluency. Writes production-grade queries without support. Does not wait on a data
team.
● Experimentation discipline. Hands-on with GrowthBook or equivalent (LaunchDarkly,
Optimizely). Understands sample sizing, guardrail metrics, and when not to ship.
● Lifecycle execution. Has personally built and shipped flows in Customer.io, Braze,
Iterable, or Klaviyo, not just briefed them.
● Copywriting instinct. Writes the SMS, the subject line, the push. Ships words, not
specs.
● Systems thinking. Reasons in loops and flywheels, not just funnels. Can articulate
where compounding comes from in a given product.
● B2B2C product sense. Has optimized for both an end consumer and a business
customer simultaneously and understands the tension between the two.
● Light engineering literacy. Python, .NET, or similar for scripting and analysis.
Comfortable working directly with engineers to instrument events and validate data.
Cultural Competencies
● Self-directed. Does not need to be told what to work on next. Finds the next experiment
on their own.
● Low ego, high ownership. Kills their own ideas when the data says so. Credits the
team when things work.
● Bias toward shipping. Prefers a shipped test to a perfect plan. Respects restraint when
the test isn't ready.
● Calm under ambiguity. This is an early-stage product inside a larger company. Comfort
with unresolved problems is required.
● Respect for the brand. This product is a quiet brand in a loud category. Growth work must
honor that — no dark patterns, no urgency manufacturing, no hype.
Nice to Have
Healthcare, wellness, aesthetics, or medspa tech background. SMS/messaging compliance
familiarity (TCPA, CTIA, A2P 10DLC). Prior experience with AI/M–L consumer products.
Referral program design experience.