DATA SCIENTIST

DATA SCIENTIST

The Data Scientist will be responsible for designing, building, and maintaining AI- and ML-powered solutions that run in production and support data-driven decisions across the Zurich organization. You will focus on creating robust data and AI pipelines, integrating existing tools and services (including LLMs), and ensuring that prototypes and proofs of concept are industrialized into secure, scalable systems. By combining strong software engineering skills with an understanding of data and AI, you will help create a solid foundation that enables innovation and business growth.

Responsibilities

• Design, develop, and deploy AI/ML-powered features, AI agents, LLM-based solutions, and analytics services in production environments.
• Build and maintain data and AI pipelines, connecting existing tools (e.g. OCR, LLM services, databases, dashboards) and ensuring reliable data flows.
• Source, collect, and analyze new data sources to support AI/ML solutions and ad hoc business questions.
• Work closely with software development teams to integrate AI/ML components into applications and platforms following engineering best practices.
• Collaborate with business stakeholders to translate complex technical concepts into actionable, user-friendly solutions and insights.
• Research, prototype, and implement emerging AI/ML technologies, particularly in generative AI and modern data engineering/data science tools.
• Contribute to data and AI roadmaps and architectural decisions to ensure scalable, secure, and maintainable solutions.

Requirements

• University degree in physics, mathematics, computer science or a related field.
• Professional experience in a related role and/or demonstrated competency (projects) utilizing relevant technologies.
• Proficient in Python, with experience building production systems and integrating APIs and services.
• Strong foundation in unstructured data processing, combining techniques such as OCR, LLM-based extraction, data format consistency, and regular expressions, along with software engineering best practices including version control, testing frameworks, and code documentation.
• Experience with machine learning tools in big data environments, with a focus on deploying and operating models/services rather than purely research.
• Practical experience with LLM APIs (OpenAI, Anthropic, etc.), prompt engineering, and response optimization.
• Experience with SQL/NoSQL databases and data modeling for production systems.
• Ability to quickly build Proofs of Concept (POCs), MVPs, and tests to demonstrate value and validate innovative solutions in an agile manner.
• Experience with dashboard and data visualization tools such as Power BI, Streamlit, or similar is a plus.
• Strong problem-solving skills, analytical mindset, and attention to detail.
• Excellent verbal and written communication skills, including the ability to explain technical issues to a non-technical audience.
• Prior experience in financial institutions, consulting firms, or other similar industries is a plus.
• Strong proficiency in both English and Portuguese is required; Spanish language skills are a plus.

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