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You will build and deploy production-ready machine learning solutions while owning the end-to-end lifecycle from data pipelines to monitoring. Additionally, you will collaborate with engineers and product managers to identify high-impact ML and GenAI opportunities to solve business problems.
Join Sport Alliance’s Data Products team and build ML solutions for Magicline and PerfectGym Next, used by thousands of fitness businesses and millions of members.
You’ll work closely with engineers and product managers to take ML use cases from idea to production, with plenty of ownership and the opportunity to shape how we use ML and AI across our products.
\nBuild and deploy production-ready ML solutions, with a focus on classical ML and statistical methods.
Own your models end-to-end — from data pipelines and modelling to deployment and monitoring.
Improve the scalability and reliability of our existing ML data pipelines.
Work closely with software engineers and product managers to turn business problems into practical solutions.
Be the Data Science expert in a small Data Products team alongside two data engineers and one data analyst.
Identify where ML and GenAI can solve real product and business problems, and choose the right approach.
Work with our platform and LLM Ops teams when additional infrastructure support is needed.
Help shape our ML and AI roadmap, identifying high-impact opportunities and influencing how ML capabilities evolve across our products.
5+ years of hands-on experience building and deploying machine learning solutions in production.
Strong knowledge of statistics and classical ML, with good judgment about which approach fits the problem, scale, and cost.
Experience owning ML projects end-to-end, including data preparation, modelling, deployment, and monitoring.
Strong hands-on Python skills (scikit-learn or similar frameworks) and SQL.
You’re proactive and comfortable working on problems that aren’t fully defined yet.
You communicate clearly and work well with both technical and non-technical colleagues.
English at C1 level or above.
Experience with AWS, Terraform, or dbt.
Experience working with LLMs or GenAI-based solutions.
German language skills.
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