Senior Data Scientist/ML Ops Engineer (all genders)

About this role

Responsibilities With a mission to empower 15.6 million house owners across Germany and the broader DACH region, we at Aroundhome are building a platform where every strategic decision is powered by data. We’re a team of around 250 people, and to take the next step, we’re looking for an experienced and hands-on Senior Data Scientist (all genders) to bring machine learning into the heart of our product. As a Senior Data Scientist, you will build Aroundhome’s first machine learning model in production: the logic that decides which partners each homeowner is matched with.

You will start from the problems homeowners and partners actually have, and own the solution end to end, in a small new team with a product manager, an engineer and the team lead. Responsibilities: Start from the Customer: Understand what homeowners and partners need from a match, and turn that into the outcomes and guardrails your models optimize for, not just model metrics. Own Our Matching Models: Build and run the models behind our partner matching, end to end: data, features, training, evaluation, deployment and monitoring.

Make Every Match Count: Improve our matching logic with deployed models that make the most efficient use of partner capacity, raise match rates, and account for regional supply and demand. Prove Impact: Measure every improvement against our current logic in controlled experiments designed for a two-sided marketplace, before it scales. Build the Data Foundation : Create the datasets and pipelines your models need, together with our engineer and the Data Engineering team.

In the first months, this is a big part of the role. Shape Our ML Stack: Decide with the team how and where models run, and set the practices for machine learning at Aroundhome. Translate Models into Decisions: Explain trade-offs between customer experience, partner fulfillment and revenue to product managers, partner category managers, key account managers and senior leadership. Skills Bachelor’s or Master’s degree or equivalent practical experience in a quantitative field (e.g., Computer Science, Statistics, Mathematics, Economics).