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Senior Data Scientist – Drug Discovery


This is a Full-time position in Cambridge, MA posted June 9, 2021.

Data Scientist Machine Learning Engineers needs for a Computational Drug Discovery Company soon closing Series A. This Jobot Job is hosted by Augie Ullmann Are you a fit? Easy Apply now by clicking the “Apply Now” button and sending us your resume. Salary 100,000 – 120,000 per year A bit about us Computation is revolutionizing drug discovery. Advances in big chemical data, massive computing power, artificial intelligence, and molecular dynamics simulation are changing the way we develop new drugs. Our client puts computation at the heart of drug discovery, blending expertise in computational chemistry, structural biology, pharmacology, genetics, data science, and software engineering to develop drugs for previously undruggable targets. We are helping our client grow their Data Scientist ML team and have three open positions. If You are someone who can act as both an Individual Contributor (IC), who can roll up their sleeves, and play an important role in our client’s mission to use AIML to develop drugs against historically difficult disease targets, read on… Why join us? Extremely generous equity package coupled with a competitive salary Healthcare benefits Generous vacation and parental leave Flexible work schedule Job Details Required Qualifications 1) 3+ years of industry experience relevant to statistical modeling andor machine learning 2) Experience in building and testing statistical andor machine learning models (support vector machines, random forests, convolutional neural networks, etc.) 3) Building andor modifying scalable machine learning architectures (CNN, LSTM, etc.) 4) Experience scaling large deep learning networks 5) Self-motivated and a proactive thinker – can work independently and in teams 6) Relevant experience in statistics and machine learning 7) Excellent written and communication skills presenting and discussing scientific data Preferred Qualifications 1) Master’s or Ph.D. degree or equivalent in relevant field 2) Previous roles in managing teams and projects 3) Knowledge in any of the following fields structural biology, immunology, protein engineering, cancer biology 4) Experience in applying computational models to protein structure data (affinity prediction, protein-protein docking, homology-based predictions, physics-based predictions) 5) Experience utilizing Amazon Web Services tools to scale and automate pipelines 6) Parallel computing strategies to accelerate data analysis Interested in hearing more? Easy Apply now by clicking the “Apply Now” button.