Description
Quiver is seeking a highly motivated Data Scientist join our Analytics Group. This Data Scientist will help develop, deploy, maintain, and effectively use tools for the analysis of all-optical electrophysiology data. This role will have a special emphasis on development of novel optical assays of neuronal electrophysiology, which will involve image processing, signal processing, and rapid prototyping. The successful applicant will work as part of a small, close-knit team at the hub of Quiver’s scientific programs to derive actionable insights from a broad range of relevant biological data modalities, including the company’s proprietary all-optical electrophysiology single cell data as well as genomics and imaging data sets. The ideal candidate will be a thoughtful and creative programmer with expertise in advanced statistical approaches, machine learning and AI methodologies. The candidate should be eager to gain practical experience across all stages of the software lifecycle and motivated to learn expansively across a wide array of skills and problem domains.
This position is based in Cambridge, MA, with the expectation of on-site presence 3-4 days per week to support lab integration, team meetings, and collaborative project work. Fully remote applicants will not be considered.
Responsibilities and Duties
Analyze electrophysiological (and other biological) data sets to serve research project goals. Make effective visualizations, draw sound inferences from complex experiments, assist biologists with experimental design and implementation, conduct reproducible analyses, and disseminate analytics findings with biologists and other stakeholders.
Contribute to all aspects of analytics software development including design, implementation, source control, performance optimization, unit testing, defect management, documentation, and ongoing maintenance and support.
Proficiently manage timelines, relationships, and work priorities to comfortably operate independently.
Utilize excellent interpersonal skills to build consensus, share insights with relevant stakeholders, deliver interpretable data products, and serve both business and scientific goals of the company with your work.
Requirements
Minimum Qualifications Required
PhD degree or corresponding demonstrable professional experience in Data Science, Computer Science, Neuroscience, (Bio)Statistics, Physics, or related technical discipline (e.g., engineering, science, or biology with a strong quantitative background).
Experience with image processing, video processing, signal processing, or time series analysis.
Comfort with multiple programming languages and computational APIs (the role will utilize Python, Matlab, R, git, SQL, and AWS, among others).
Experience developing complex data pipelines or analysis tools.
Broad experience with commonly used data science and machine learning toolkits, libraries, and frameworks (sklearm, pytorch, statsmodels etc).
High level of creativity, with a passion for neuroscience or other biomedical fields.
Excellent skills in the areas of verbal/written communication, problem solving, and leadership.
Additional Qualifications Desired
Knowledge and experience in biophysics, physiology, or neuroscience, especially electrophysiology or high-content imaging.
Experience integrating complementary data streams. (e.g., transcriptomics, high-content imaging, clinical datasets, etc.) using knowledge graphs or advanced statistical, machine learning, and AI methods.
Comfortable with linear algebra and probability theory.
Experience with statistical analysis and techniques for inference (including regression, splines/smooths, bootstrap and permutation methods, power analysis, theory of experimental design etc).
Experience with deep-learning and neural network models, including modern convolutional models, unsupervised/self-supervised learning approaches, data augmentation, and current best-practices for training and optimization.
