The Operations group at the Yale School of Management is seeking a pre-doctoral research associate to support quantitative research with a focus on healthcare operations and sports analytics. The Research Associate will work closely with Operations Professors Lesley Meng and Nils Rudi.
As a Research Associate, you will have a variety of responsibilities that will keep you engaged and challenged. Your role will involve conducting statistical and econometric analyses, collecting and cleaning data for analysis, creating visually appealing data visualizations, conducting background research, and managing large databases.
You will support research projects spanning a broad range of topics, including healthcare operations, sports analytics, and empirical learning studies. For example, you may be tasked with investigating how staffing or operational decisions in hospital emergency departments impact patient care quality outcomes, or exploring the effects of pressure on soccer penalty shootout performances and the influence of the number of sets played in tennis on performance outcomes. You will also have the opportunity to delve into the fascinating realm of how individuals learn and reason about quantitative subjects, with a particular focus on problem solving within probability theory.
The ideal candidate for the pre-doctoral research associate position should have a strong desire to expand and deepen their research and quantitative data analysis skills while working for a period of 1-2 years. A successful candidate will be well-prepared to apply for PhD programs in areas such as Operations, Economics, Quantitative Marketing, or Statistics and Data Science upon completion of the position.
As a Research Associate, you will have the opportunity to become an active member of the Yale SOM research community. This may include attending seminars, exploring personal research interests, and taking graduate-level courses at Yale. You will also have the privilege of joining a cohort of pre-doctoral Research Associates from diverse areas who will work alongside you, providing a dynamic and stimulating intellectual environment.
REQUISITE SKILLS AND QUALIFICATIONS:
To be considered for the position, the successful candidate should possess a minimum of a Bachelor’s degree in a relevant field such as operations research, statistics, computer science, engineering, or other data science-related fields. Holding a Master's or other graduate degree would be a plus.
In addition to your educational qualifications, you should have an active working proficiency in one or two major statistical programming languages, such as R, Python, or Julia. You should also have expertise in databases, particularly in SQL.
The ideal candidate should have prior experience writing code to assist with the cleaning and organization of large datasets. Additionally, you should feel comfortable using basic statistical modeling techniques, such as regression. Experience with Bayesian inference and packages such as PyMC, Stan, Turing.jl, GEN, Birch, or Nimble would be considered an advantage.
SPECIAL APPLICATION INSTRUCTIONS: