3 data analyst jobs found in Zürich

Note: By applying to this position you will have an opportunity to share your preferred working location from the following:   Mountain View, CA, USA; New York, NY, USA; Zürich, Switzerland . Minimum qualifications: Master's degree in a quantitative discipline such as Statistics, Engineering, Sciences, or equivalent practical experience. 4 years of experience in data analysis or data science, including identifying trends, generating summary statistics, and drawing insights from quantitative and qualitative data. Preferred qualifications: Ability to present to executives with clear communication, with a demonstrated track record of cross-functional stakeholder management and leadership through influence. About the job Artificial intelligence will be one of humanity’s most transformative inventions. At Google DeepMind, we are a pioneering AI lab with exceptional interdisciplinary teams focused on advancing AI development to solve complex global...

At Julius Baer, we celebrate and value the individual qualities you bring, enabling you to be impactful, to be entrepreneurial, to be empowered, and to create value beyond wealth. Let’s shape the future of wealth management together. Do you aspire to be part of a high performing Analytics and Transformation team within a global Compliance organisation at the forefront of the wealth management industry? In this diverse role you will implement new technologies, manage change initiatives, develop predictive models, and perform financial and economic analysis to increase the efficiency and effectiveness of risk management. Working alongside Risk, Compliance, Analytics and Legal SMEs in highly skilled, fast-paced teams you will drive business value through collaboratively solving complex analytical problems. YOUR CHALLENGE Lead and support data analytics and business intelligence initiatives to success, with focus on Non-Financial Risk (e.g., Anti-Money Laundering (AML),...

The team you will join, Proteus, is building a product that powers the model-based work of our internal sector experts: scientists and domain specialists who understand environmental data deeply but are not software engineers. Your job is to build the tooling they use, mentor them in software practice, and help them own production end-to-end. This is hands-on engineering work with a coaching element. You will write production-quality Python, build and maintain data pipelines, collect requirements from domain experts directly, and help people who are not from a software background ship work they can be proud of. This is not a role where requirements land neatly in a ticket and you implement them in isolation. It is not a heads-down engineering position with no stakeholder interaction. If you prefer a fully defined process and minimal ambiguity, this will not work for you. What you will be working on Design and build Python tooling that sector experts use to implement...