About us
Apomeds is an online clinic with its own pharmacy: online consultation, prescription and
delivery in one flow. We work in 7 European markets (Germany, UK, Switzerland, Sweden,
Denmark, Portugal, Lithuania) in men’s health and weight loss, with 100k+ paying
customers a year and a subscription model at the core of the business.
Analytics at Apomedical is AI-native. We run Claude Code on top of our data warehouse
with our own library of analytics skills: the rules of our data model, funnels, cohorts, A/B
test analysis and the marketing metrics we report every day are encoded there. The
assistant drafts the SQL and the first cut of an analysis; you own the question, the data
traps and the correctness of the number that goes to the team. You will spend your time
on decisions, not on boilerplate.
Our stack: PostgreSQL, Python, DBT, Tableau, Superset, Clarity, Claude
The role
As a Junior Product Analyst, you’ll work closely with the product and marketing teams to
make data-driven decisions that improve the user experience and help the business grow.
What you’ll do
- Find where users drop off in the flow, and suggest what to fix to improve conversion.
- Help design and analyze A/B tests on UX and pricing.
Build and maintain dashboards in Superset and Tableau that product and marketing
teams use every day. - Track core product and marketing KPIs (conversion rate, retention, CPA) and
investigate when one moves unexpectedly. - Translate findings into product recommendations.
- Present findings to non-technical stakeholders.
What we’re looking for
- 6 months to 2 years of experience as a product, data or BI analyst.
- Solid SQL: joins, aggregations, CTEs and window functions. You will review a lot of SQL
that you did not write, so you need to read it fluently. - Statistics basics: hypothesis testing, p-values, confidence intervals, and why sample
size matters. - Hands-on experience with at least one BI tool (Tableau, Superset, Looker or Power BI).
- Understanding of core product and unit-economics metrics: conversion, retention,
churn, LTV. - Comfortable working with AI assistants for SQL, analysis and writing, and in the habit
of verifying their output against the data. - Ability to turn your analysis into a business recommendation.
- Fluent English.
Nice to have
- Python for data analysis.
- Experience with event-based analytics.
- Experience with A/B tests
- Experience building your own AI workflows: prompts, skills or scripts that automate
repetitive analysis