Analytics for grocery groups. You turn model outputs into a product a buyer will open before the Monday trade meeting.
Illustrative photo, Wikimedia Commons. Not Orchard.
Discipline
Product
Place
Berlin
Type
Permanent
Salary
€100–120k
The company
Orchard forecasts demand for supermarkets. The models are strong and the product around them is a collection of notebooks and a tired dashboard. This hire makes it a product.
The team
Two data scientists, one designer, three engineers. You report to the head of product.
First months
Sit with two buyers in stores, pick the Monday view, and ship it. Everything else waits.
The work
Decide what a buyer sees on Monday morning
Translate model limits into product language without sanding them off
Prioritise with the science lead, not around them
Visit stores. The data is about apples and closing times
You will likely have
Product experience next to data or ML teams
You have shipped a surface non-analysts use
Berlin hybrid, three days
German helps with buyers. English runs the company
Two doors. Same desk.
Hiring managers send a brief. Candidates send a CV. A person reads both.
