Data Science Software Engineer Immunetrics
Designing, developing, and maintaining algorithms for computational/statistical analysis of mathematical models and clinical data
Applying machine learning techniques to analyze multivariate time series data
Contributing to general software engineering efforts to build backend infrastructure for simulation of mathematical models
Working with scientific user-base and architects to solicit new features and improve users' workflow
Rapid prototyping of next-generation experimental features
Analyzing algorithm performance and optimizing code for computational efficiency
Responsible for all aspects of software process: design, prototyping, debugging, testing, documentation, etc.
Helping end-users troubleshoot problems
Minimum of BS in Computer Science; MS preferred. Strong statistics and mathematics background beyond standard undergraduate CS curriculum is required.
Experience with machine learning projects is required.
Strong background in algorithms, data structures, and software engineering principles is essential.
Commitment to writing elegant, reliable, robust software is essential.
Solid object-oriented design skills, testing and debugging skills are required.
Applicant should be a proficient programmer in at least one of the following languages: Python, C++, or Java.
Eagerness to work in a team-oriented, small company environment
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Pittsburgh, PA 15213