Lead Data Scientist, Personalization & Customer Algorithms

Myjob; Zürich; Vor Ort; CHF 180.000 - 260.000; Vollzeit

Benefits dieser Stelle

Growth environment

Equal opportunity employer

Thorough interview process

Zusammenfassung

On is seeking a Principal Data Scientist to shape the strategy for personalization and customer algorithms across our global platforms. You will architect, train, and deploy both batch and real-time models, partnering with Product Management and Tech Partnerships to solve high-impact customer needs.

You will lead complex, cross-functional initiatives, driving measurable business outcomes and mentoring teams in MLOps and modern ML stacks across Python, PyTorch, JAX, and TensorFlow.

Qualifikationen

• 10+ years of experience building and shipping personalization engines and predictive models.
• Proven ability to deploy real-time ML models and manage end-to-end ML pipelines.
• Strong track record partnering with product management and tech partnerships.

Aufgaben

• Chart the vision for personalization and customer-level algorithms aligned with business goals.
• Design, train, and deploy batch and real-time ML models into production with governance.
• Partner with Product Management and external Tech Partnerships to translate challenges into solutions.
• Drive measurable business outcomes and customer value across touchpoints.
• Lead cross-functional teams and set standards for MLOps and QA metrics.
• Mentor data science and engineering colleagues to raise technical standards.

Kenntnisse

Python

ML libraries

Cloud platforms

Kafka

MLOps

PyTorch

JAX

TensorFlow

Generative AI

Real-time training

Jobbeschreibung

On is seeking a Principal Data Scientist to shape the strategy for personalization and customer algorithms across our global platforms. You will architect, train, and deploy both batch and real-time models, partnering with Product Management and Tech Partnerships to solve high-impact customer needs.

You will lead complex, cross-functional initiatives, driving measurable business outcomes and mentoring teams in MLOps and modern ML stacks across Python, PyTorch, JAX, and TensorFlow.