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Position Title: Principal Scientist - Machine Learning
City: Cambridge
Region: Massachusetts
Country: USA

About Pfizer:
A career at Pfizer offers opportunity, ownership and impact. All over the world, Pfizer colleagues work together to positively impact health for everyone, everywhere. Our colleagues have the opportunity to grow and develop a career that offers both individual and company success; be part of an ownership culture that values diversity and where all colleagues are energized and engaged; and the ability to impact the health and lives of millions of people. Pfizer, a global leader in the biopharmaceutical industry, is continuously seeking top talent who are inspired by our purpose to innovate to bring therapies to patients that significantly improve their lives.
Role Description:
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.

  • Leverage the scale of Pfizer proprietary data and compute infrastructure in conjunction with commercial tools and external data sources to address challenging drug discovery problems.
  • Explore traditional statistical modeling, machine learning, and deep learning algorithms to develop predictive models and generate useful insights for compound design using our vast collection of compound screening and crystal structure databases.
  • Develop and apply theoretical and machine learning techniques for modeling and prediction of important physicochemical properties of small molecules and monoclonal antibodies, protein-ligand binding affinity, polyphamacology, and analysis of high volume data generated by various screening efforts.
  • Build predictive models form large-scale operational data from Medicinal Sciences.
  • Develop methods and tools to support analysis and visualization of large datasets.
  • Remain current with respect to literature; proactively identify, assess, and internalize promising methods and tools.
  • 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.
  • Excellent communication and interpersonal skills.

EEO & Employment Eligibility:
Pfizer is committed to equal opportunity in the terms and conditions of employment for all employees and job applicants without regard to race, color, religion, sex, sexual orientation, age, gender identity or gender expression, national origin, disability or veteran status. Pfizer also complies with all applicable national, state and local laws governing nondiscrimination in employment as well as work authorization and employment eligibility verification requirements of the Immigration and Nationality Act and IRCA. Pfizer is an E-Verify employer.