We are a U.S.-based product company. Our product, a next-generation data analytics platform, is used by the biggest pharma companies and is strongly connected to natural sciences. We are looking for a talented data scientist that will join our strong team and help us build the revolutionary product (check out datagrok.ai, you’ll be surprised) with the emphasis on R&D in life sciences, cheminformatics, healthcare, biomedical research, biosensors, and other areas.
✔ Zero bureaucracy, flexible working hours without tracking, full-remote work.
✔ No formal restrictions on sick leaves.
✔ Excellent growth opportunities in a highly dynamic, unique product company.
✔ Competitive compensation
• Masters degree with a minimum of 3 years of relevant experience in Computer Science, Statistics, Machine Learning & Artificial Intelligence, Physics, Mathematics, Computational Chemistry, Bioinformatics, Computational Biology or a related discipline is required.
• Ph.D degree with the relevant research experience is a big plus.
• Cheminformatics, drug discovery, or clinical development experience is a big plus.
• Strong working knowledge of machine learning algorithms such as Random Forest, SVM, neural networks, etc. and/or Natural Language Processing techniques is required.
• Proficiency with one or more programming languages such as Python, R, C++, or Java is required.
• Experience in web development, including UI and UX, is a plus.
• Experience with visualization software/tools such as R, Spotfire, Tableau, etc. is preferred.
• Ability to effectively communicate technical work to a wide audience is required.
• Use predictive modeling, statistics, machine learning, data mining, and other * data analysis techniques to collect, explore, extract, report insights from structured and unstructured data.
• Develop and apply creative solutions that go beyond current tools to deliver data-driven insights to high-priority scientific problems.
• Collaborate with cross-functional teams (customers, internal IT teams, etc) to understand business needs, ensure data integrity and flow efficiency, and to create reports/tools for customer utilization.
• Present finding and recommendation to customers and internal management teams.
• Develop high-performance, production code.