Data Scientist (AI/ML)

Location: Zurich, Switzerland

Company

hirify.global is a financial services organization shaping enterprise data science capabilities for wealth management.

What you will do

• Define and maintain the technical vision, roadmap, and lifecycle strategy for the enterprise data science workbench.
• Gather requirements from platform consumers and translate business ambitions into technical capabilities.
• Lead feature prioritization and delivery across Agile platform, engineering, architecture, and release teams.
• Ensure scalability, reliability, performance, security, observability, automation, and resilience by design.
• Establish SLAs, SLOs, KPIs, governance, incident processes, and the target operating model.
• Act as the technical escalation point for incidents, audits, risk findings, and operational issues.

Requirements

• Bachelor’s or master’s degree in computer science, information systems, or a related field.
• At least 5 years of experience in technology or data science roles within large, regulated enterprises, preferably financial services.
• Experience designing and operationalizing AI and ML platforms, MLOps pipelines, model lifecycle frameworks, and governed model development environments.
• Hands-on expertise with Python, R, SQL, TensorFlow, PyTorch, Scikit-learn, and modern data lake or data lakehouse technologies such as Spark, Iceberg, Trino, Kafka, Kubernetes, Snowflake, or Databricks.
• Experience with LLM integration, generative AI, prompt engineering, statistical modelling, predictive analytics, NLP, feature stores, vector databases, and AI orchestration tools.
• Fluent English required; German is an advantage. Experience with Swiss financial-sector risk, compliance, and audit requirements is expected.

Culture & Benefits

• Work in a matrixed, multinational financial-services environment.
• Collaborate with platform owners, product owners, architects, engineering teams, external partners, and business stakeholders.
• Balance innovation, agility, compliance, sustainability, and operational resilience.
• Contribute to a data science community of practice across the organization.