Data Scientist
- Job Type: Officer of Administration
- Bargaining Unit:
- Regular/Temporary: Regular
- End Date if Temporary:
- Hours Per Week: 35
- Standard Work Schedule:
- Building:
- Salary Range: 64,350 – 66,300
The salary of the finalist selected for this role will be set based on a variety of factors, including but not limited to departmental budgets, qualifications, experience, education, licenses, specialty, and training. The above hiring range represents the University’s good faith and reasonable estimate of the range of possible compensation at the time of posting.
- Job Type: Officer of Administration
- Bargaining Unit:
- Regular/Temporary: Regular
- End Date if Temporary:
- Hours Per Week: 35
- Standard Work Schedule:
- Building:
- Salary Range: 64,350 – 66,300
The salary of the finalist selected for this role will be set based on a variety of factors, including but not limited to departmental budgets, qualifications, experience, education, licenses, specialty, and training. The above hiring range represents the University’s good faith and reasonable estimate of the range of possible compensation at the time of posting.
Position Summary
The successful candidate will work in close collaboration with scientists in the Movement Recovery Laboratory on projects at the intersection of neuroscience and biomedical engineering. An initial goal will be to model neurostimulation recruitment-curve relationships by extending Bayesian recruitment curve methods to paired cortical–spinal stimulation and by building a researcher-friendly GUI around our existing Python library hbMEP.
Responsibilities
- Developing analysis pipelines for electrophysiological data from rats and humans.
- Implementing, developing, and validating hierarchical Bayesian models of motor-evoked potential (MEP) recruitment curves.
- Creating interactive visualization and dashboard tools.
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Data mining, statistical analysis, and mathematical modelling.
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Provides support for use of developed methods.
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Remains up to date on the scientific literature of statistical methods and machine learning as applied to electrophysiology
Minimum Qualifications
- Requires a bachelor’s degree or equivalent in education and experience
Preferred Qualifications
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MSc degree in data science or equivalent qualification.
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Development of analysis pipelines (Python preferred).
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Experience with Bayesian Generalized Linear Models (NumPyro, RSTAN preferred).
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Experience with developing visualization of electrophysiological data (e.g. tableu, matlab, matplotlib).
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Experience with git and ability to work collaboratively on software.
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Must be able to communicate verbally and in writing in a professional and succinct manner and be open to feedback and collaboration.
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Adept at solving problems quickly, efficiently, and independently.
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Equal Opportunity Employer / Disability / Veteran
Columbia University is committed to the hiring of qualified local residents.
