Doctoral Student in Operational Decision Making with Data Science

Develop new methods for experimental and causal evaluation that are relevant in real business. Write high-quality papers and publish on top-tier OM journals. Work with industrial partners on implementing the methods if needed. They will also have the opportunity to develop their own research questions within the broader topic of the data-driven decision making. In addition to research activities, they will contribute to light tasks and responsibilities (e.g. teaching, lab activities).

The Decision Sciences and Analytics group, led by Prof. Tu Ni at ETH Zürich is seeking a doctoral student to study operational decision making with data science. This position focuses on the development of experimental and causal methods for efficient and robust evaluation of new product, policy, and technology in modern operational context of organizations. The research is mainly theoretical, but connected to several industrial applications in online marketplaces. ETH Zurich is one of the world’s leading universities specialising in science and technology. We are renowned for our excellent education, cutting-edge fundamental research and direct transfer of new knowledge into society. Over 30,000 people from more than 120 countries find our university to be a place that promotes independent thinking and an environment that inspires excellence. Located in the heart of Europe, yet forging connections all over the world, we work together to develop solutions for the global challenges of today and tomorrow.

• Hold (or will have completed at the time of appointment) a Master’s degree in statistics, operations, economics, or a closely related field

• Excellent academic records and is motivated to produce high-quality, policy-relevant research

• Have excellent quantitative skills: statistics, optimization, stochastic modeling, etc

• Have excellent verbal and written communication skills

• Have experience in working on real A/B testing is a plus