Data Scientist 100% (f/m/d)

In this role you will shape and govern Julius Baer’s enterprise data science workbench within the Global Data Platform. You will define the technical vision, roadmap, and community of practice to enable data-driven decision-making and robust reporting across the bank. You’ll balance innovation with compliance, scalability with reliability, and fast delivery with sustainable operations. You will collaborate with cross-functional partners to ensure platform health, governance, and alignment with regulatory standards. This is a pivotal opportunity to lead a data science platform that accelerates advanced analytics across a regulated, multinational bank.

• Define and maintain end-to-end technical vision, roadmap, and lifecycle for the data science workbench within the global data platform
• Gather requirements and engage with current and potential consumer base to align the roadmap with business ambitions
• Ensure platform scalability, reliability, performance, and security, embedding NFRs, observability, automation, and resilience-by-design
• Prioritize and deliver data science workbench features across Agile teams in collaboration with Platform Owner, Scrum Masters, and engineers
• Own and drive the community of practices for the data science workbench across the organization
• Serve as the primary technical escalation point for incidents, audits, and risk findings related to the data science workbench
• Establish and monitor SLAs, SLOs, and KPIs; use metrics and OKRs to measure platform health and business value
• Drive standardisation and reuse across the ecosystem to reduce complexity and accelerate time-to-market
• Shape the target operating model for data science workbench operations, including governance, RACI, incident triage, and handover processes

• Bachelor's or Master's degree in computer science, Information Systems, or a related field
• Minimum of 5 years of experience in technology and/or data science roles in large, regulated enterprises (preferably financial services)
• Proven experience designing and operationalising AI/ML platforms, MLOps pipelines, and model lifecycle management frameworks
• Hands-on experience with Python, R, SQL and libraries like TensorFlow, PyTorch, Scikit-learn
• Experience with LLM integration, generative AI frameworks, and enterprise prompt engineering
• Strong background in statistical modelling, predictive analytics, and NLP
• Experience implementing responsible AI practices including model validation, bias detection, and explainability in regulated contexts
• Track record of enabling data science teams by building scalable, governed environments for model development, training, and deployment
• Experience with feature stores, vector databases, and AI orchestration tools
• Ability to translate complex data science and AI requirements into robust, production-grade infrastructure specifications
• Proven experience leading and scaling a community of practice
• Track record with defining and delivering technical visions and roadmaps in enterprise environments
• Hands-on exposure to modern datalake/datalake-house technologies (e.g., Spark/Iceberg, Trino, Kafka, Kubernetes, Snowflake/Databricks, Hadoop)
• Strong understanding of Agile, DevOps, CI/CD
• Familiarity with risk and compliance frameworks for Swiss financial institutions and addressing audit points
• Excellent technical leadership and systems thinking; able to balance short-term delivery with platform sustainability
• Good communication skills across levels; able to discuss both business summaries and technical details
• Expertise in software lifecycle governance, technical debt management, vulnerability remediation, and release approval processes
• Skilled in roadmapping, dependency management, and translating business capabilities into technical initiatives
• People-oriented with comfort in significant business/consumer interaction
• Understanding of non-functional requirements: performance, availability, recoverability, monitoring, logging, security-by-default
• Strong analytical mindset with data-informed decision-making using KPIs and telemetry
• Fluent in English; German an advantage
• Ability to operate in a matrixed, multinational environment with competing priorities

• communication
• leadership
• collaboration
• Python
• R
• SQL