Doctoral Student in Operational Decision Making with Data Science

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.

Job description

• 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)

Profile

• 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

Workplace

Workplace

We offer

• The starting date is negotiable
• The position is initially offered for 18 months, with the prospect of extension for four- to five-year duration of the doctorate, subject to satisfactory progress
• We offer the opportunity to pursue a high-quality PhD at a renowned institution and to work in a dynamic and collaborative research environment
• Gross salary will be in accordance with the regulatons of ETH Zurich

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