Data Scientist 100% (f/m/d)

Julius Baer is seeking a full‑time Data Scientist to shape the future of its Global Data Platform's data‑science workbench. The bank focuses on wealth management and values entrepreneurial, empowered individuals who can create value beyond wealth. In this role you will define and maintain the end‑to‑end technical vision, roadmap and lifecycle strategy for the workbench. You will gather requirements from current and potential users, ensure platform scalability, reliability, performance and security, and embed observability, automation and resilience‑by‑design. You will lead the prioritisation and delivery of new features, coordinate with platform owners, Scrum Masters, development teams and external partners, and act as the primary technical escalation point for incidents, audits and risk findings. You will also establish and monitor SLAs, SLOs and KPIs, drive standardisation and reuse across the ecosystem, and shape the operating model for governance, incident triage and hand‑over processes. The ideal candidate holds a bachelor's or master's degree in Computer Science, Information Systems or a related field and brings at least five years of experience in technology or data‑science roles within large, regulated enterprises, preferably in financial services. You must have proven experience designing and operationalising AI/ML platforms, MLOps pipelines and model‑lifecycle frameworks, as well as hands‑on expertise in Python, R, SQL and libraries such as TensorFlow, PyTorch and Scikit‑learn. Experience with Large Language Model integration, generative AI, statistical modelling, predictive analytics and NLP is required, together with a track record of implementing responsible‑AI practices, building scalable governed environments, and using feature stores, vector databases and AI orchestration tools. Strong knowledge of modern data‑lake technologies (Spark, Iceberg, Trino, Kafka, Kubernetes, Snowflake/Databricks), Agile, DevOps and CI/CD, as well as Swiss financial risk and compliance frameworks, is essential. Excellent communication, technical leadership, systems thinking and the ability to translate complex AI requirements into production‑grade infrastructure are also mandatory. Nice‑to‑have attributes include German language skills, a people‑oriented mindset for extensive business and consumer interaction, and a solid understanding of non‑functional requirements such as performance, availability, recoverability, monitoring, logging and security‑by‑default. The position operates in a matrixed, multinational environment with competing priorities, offering the chance to lead a community of practice and influence the bank's data‑driven decision‑making. What the role asks for: - Bachelor's or Master's in Computer Science, Information Systems or related - Minimum 5 years experience in technology or data‑science at large regulated firms - Design and operate AI/ML platforms with MLOps pipelines - Proficient in Python, R, SQL and TensorFlow/PyTorch/Scikit‑learn - Experience integrating Large Language Models and generative AI - Strong statistical modelling, predictive analytics and NLP expertise - Implement responsible AI: validation, bias detection, explainability - Build scalable, governed environments for model development and deployment - Use feature stores, vector databases and AI orchestration tools - Translate AI requirements into production‑grade infrastructure specs - Lead and scale a community of practice - Define and deliver technical visions and roadmaps enterprise‑wide - Hands‑on with Spark/Iceberg, Trino, Kafka, Kubernetes, Snowflake/Databricks - Apply Agile, DevOps and CI/CD practices - Knowledge of Swiss financial risk and compliance frameworks - Demonstrated technical leadership and systems thinking - Excellent communication for management and technical audiences - Govern software lifecycle, manage technical debt and vulnerabilities - Road‑map, manage dependencies and convert business needs to technical plans - Comfortable with extensive business/consumer interaction - Understand non‑functional requirements: performance, availability, security‑by‑default - Strong analytical mindset using KPIs and telemetry - Fluent English (written and spoken) - German language skills, advantage (nice‑to‑have)