The Pfizer Computational Sciences group has an opening for a data scientist with expertise in machine learning. The successful candidate will work in close collaboration with groups across Medicinal Sciences organization and will utilize his/her machine learning, data analysis, and scientific programming experience to address challenging problems covering a wide range of research and development activities within Pfizer R&D. To be successful in this role, the incumbent must have the talent and skills to analyze large, multi-dimensional datasets from internal and external sources and to rapidly develop effective in silico models and implement powerful computational solutions.
- Ph.D. in computational chemistry, computer science, physical or biological sciences, machine learning, or related discipline with 0-3 years of relevant experience required.
- Familiarity with several machine learning algorithms and packages (e.g. Regression and Classification algorithms, Supervised and Unsupervised learning algorithms, Random Forest, Support Vector Machine, Neural Networks, Deep Learning, Sci-kit Learn, R, MATLAB, Theano, TensorFlow).
- Experience working with large data sets, preferably in drug discovery setting.
- Experience with Unix/Linux, HPC environments, and high-level programming language (e.g. Python).
- Demonstrated track record of applied machine learning and data science through publications in top tier peer-reviewed journals and/or presentations in national or international conferences.