On AG
Principal Data Scientist
Zürich · ZH
- Berufsfeld
- Informatik · Data & Analytics
- Ausbildung
- Keine bestimmte Ausbildung
- Erfahrung
- Über 5 Jahre
- Sprachkenntnisse
- Englisch
- Lohn
- Geschätzt CHF 200’000–250’000 pro Jahr (100 %)
- Schätzung von jopp, nicht aus dem Inserat.
- Veröffentlicht am
- 09. September 2026
- Zuletzt gesehen
- 18. September 2026
In short As a Principal Data Scientist specializing in Personalization and Customer Algorithms, your mission is to set the strategic direction for customer modeling across On. You will lead high-impact initiatives to architect, train, and deploy personalization algorithms that deliver direct, measurable impact to our business and customers. Operating at the intersection of technology, product management, and commercial strategy, you will simplify technical complexity, navigate an evolving technology landscape, and partner with key product and technology partners to ensure we build algorithms that solve the right problems for our global customer base. Your Mission Chart the vision for personalization and customer-level algorithms, ensuring all projects align seamlessly with On-s broader commercial goals and north star tech strategy. Lead complex initiatives to design, train, and deploy batch and real-time machine learning models into well governed production environments. Partner closely with Product Management and external Tech Partnerships to deeply understand core business challenges and design algorithms that directly solve high-impact customer needs. Focus relentlessly on driving quantifiable business outcomes and customer value across every touchpoint, from web and app to personalized customer messaging. Evaluate how we adopt and integrate changing commercial technologies and partner platforms. Break down complex data science architectures and machine learning concepts to bring cross-functional leadership, product teams, and business partners along on the journey. Act as a core technical authority on wider-On decisions, establishing standards for real-time model training, MLOps infrastructure, and algorithmic QA metrics. Mentor and guide data science and engineering talent across the organization, fostering high technical standards and a culture of continuous learning. Your story You have 10+ years of experience in building and shipping personalization engines, recommendation systems, and customer-level predictive models in a fast-paced D2C or E-commerce environment. This should include real-time model training, streaming data processing, and deploying low-latency machine learning models to production systems. Proven track record of working side-by-side with Product Management and Tech Partnerships to translate ambiguous business challenges into solutions that have measurable large scale impact on key company KPIs. Strong history of defining success metrics and validating customer impact through rigorous experimentation, A/B testing, and continuous feedback loops, in partnership with analytics and product teams. Proven ability to lead complex, company-wide initiatives, influence senior business leaders, and drive strategic consensus across multi-disciplinary teams. Advanced proficiency in Python, modern machine learning libraries, cloud environments (e.g., GCP, AWS), event-driven architectures (e.g., Kafka), and end-to-end MLOps practices, PyTorch, JAX & Tensorflow. Experience in both deploying Generative AI in customer applications, and using generative AI to accelerate engineering delivery workflows. Outstanding storytelling and presentation skills, with the ability to explain complex algorithmic behavior clearly to technical and non-technical stakeholders alike. About the Team We are a fast-growing, collaborative team of Data Scientists and Machine Learning Engineers sitting within Technology. We build creative, end-to-end ML and Generative AI models that personalize customer experiences, optimize commercial decision-making, and predict future trends across On-s global ecosystem. We thrive in an energetic, fast-paced environment where technology is seen as a key driver of innovation and customer delight. See more