Data Scientist
Build and ship models that predict user value, engagement, and reward behaviour.
Build and ship models that predict user value, engagement, and reward behaviour.
Why voize? Because we’re more than just a job!
The Ranking team at Zalando assists customers in their fashion discovery journey and helps them find what they are looking for.
will be dynamic and deeply technical, placing you at the center of compiler innovation.
Make an Impact by: In this role, you will develop models and insights that help predict charging behavior, optimize billing, and improve customer engagement.
Wir schreiben dir, sobald eine neue geprüfte Stelle in Berlin dazukommt. Höchstens eine Nachricht am Tag, und nur, wenn es tatsächlich etwas Neues gibt.
Abmelden mit einem Klick, jederzeit. Keine Weitergabe an Dritte.
Job Title: System Integrator / Software Engineer – Robotic Hand (m/f/d) Location: Berlin, Germany Why this role matters Having secured disru
Leitet ein internationales Risk-Analytics-Team, entwickelt Risikostrategien und unterstützt ML-basierte Modelle für die Kreditentscheidung.
Airteam is a Berlin-based SaaS startup with an AI-powered cloud platform for roofers and solar planners.
Du arbeitest gemeinsam mit uns an Projekten für Kunden aus dem Gesundheitswesen, zum Beispiel: Analysen und ML-Modelle auf echten Versorgung
RoboService solves the Last Mile of humanoid robotics.
We re looking for a Data Scientist who treats AI as a working tool, not a buzzword.
Verwaltungssprung is a Berlin-based GovTech company developing AI-powered software solutions to simplify and digitize administrative processes.
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Warum dieser Job gelistet ist
Eindeutige KI-Rollenbezeichnung im Stellentitel. Prüfverfahren ansehen
Build and ship models that predict user value, engagement, and reward behaviour. See them live in production. - Design and run A/B tests on offers, rewards, and ranking. Work out what actually caused the result through causal reasoning. - Build data infrastructure and measurement systems that let you reason rigorously about impact. - Own undefined product problems from first idea to production.
No playbook. You own it all. What You ll Bring - Strong Python and SQL.
You use AI tools to move faster, and you still verify the output. - Research or academic background with proof of depth: published work, thesis, strong coursework, or competition results. - You get going on a vague problem without waiting for a spec, and you take it further than you were asked. - You quickly see which number matters and which question to answer first. - You think in causation and testable hypotheses. You debug rigorously when things break. - Bonus: Kaggle competition results, published papers, thesis work, or a system you built and hardened yourself. Why Almedia - A small, selective team of very sharp people.
We keep it small on purpose, so every hire raises the bar - Equity in Almedia. Every Berlin-based employee gets a stake, so you share in what you help build - Top-of-market pay as the baseline. Outlier impact gets paid accordingly Small team, high bar.
If that sounds like home, apply. We believe in fostering talent, evaluating all skill levels during the hiring process, and providing a clear path for growth. Almedia is an equal opportunity employer.
We embrace and celebrate diversity, and encourage individuals from all backgrounds to apply.
Our bar is high, and this is the best place for ambitious builders. Bootstrapped and profitable from day one, Almedia is Germany’s fastest-growing company (FT1000). Join us as we build the global leader in rewards, at a $1bn+ revenue run rate and climbing fast.
Data Scientist Berlin, On-site You ll join a small team of people who have built and shipped ML systems at scale. You ll work on real problems from week one with the support to solve them. Show us you can own more, and we ll give you more.
Interesse an dieser Position?
Die vollständige Anzeige und das Bewerbungsformular liegen beim Arbeitgeber.
Zur Originalanzeige84 geprüfte Stellen bei 58 Arbeitgebern, 5 davon ortsunabhängig. Modelle bauen, trainieren und verbessern: von klassischem Machine Learning über Computer Vision bis zum Feinschliff großer Sprachmodelle.