The Research Associate (RA) position reports directly to faculty supervisors in the Marketing unit and administrative manager in the Research Staff Services office. Ideal RA candidates will be comfortable in an environment that requires a high level of independence, intellectual curiosity, and the ability to use discretionary judgment. Under the general direction of faculty member(s), RAs will develop, design and conduct research projects; conduct experiments, collect and label big data; synthesize, analyze, and produce statistical models; contribute to scholarly research products including but not limited to journal articles, working papers, and presentations.
Work under the general direction of a faculty member in the Marketing unit on topics central to HBS research agenda.
Independently manage all timelines and deliverables. Exercise independent decision making with regard to progression of research project and methodologies. Must be able to structure assignments and keep faculty member informed as necessary, using own judgment.
The qualified individual should demonstrate strong skills of:
Statistical analysis and data mining, including STATA, MATLAB, and R.
Programming and engineering, including Python, Bash script, SQL, and preferably C++ and Hadoop/Hive experience.
Machine learning, including understanding in common ML models (e.g. BST, RCNN), as well as experience in OpenCV and Caffe.
Strong background in mathematics.
Develop, synthesize, and provide analysis of data exhibits for academic journal articles. RA must also ensure compliance with department, University, and federal regulations. Complete work with only general direction. Be aware of department, School, University policies and potential outside research policies.
Bachelor’s degree required. Strong preference for candidates with a background in Computer Science or Econometrics.
The candidate must have extremely high standards in terms of quality of work, especially concerning data quality. He or she will work on projects involving collecting, experimenting and analyzing very large sets of diverse data from retail stores, combining a range of state-of-art sensor fusion, computer vision/machine learning technologies, and statistical analyses to understand consumer behavior.
Attention to detail, strong organizational skills, and absolute commitment to task completion are a must. Evidence of outstanding academic achievement, strong mathematics background, and the ability to establish strong engineering and research skills in big data are essential.
This is a half-time term appointment starting as soon as possible and ending June 30, 2018 with potential for reappointment.
Half-time positions can be paired to create a full-time position.
Preference for candidate who plans to seek an advanced degree.
HBS is not able to provide visa sponsorship for this position.
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We are an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability status, protected veteran status, gender identity, sexual orientation or any other characteristic protected by law.