Computational Data Expert
6 days ago
Estimated salary for this position is $120,000 - $180,000 per year.
About the CompanyiSoftTek Solutions Inc is a leading provider of data science solutions in the pharmaceutical industry. Our team of experts works closely with clients to develop innovative IT systems and platforms that support scientific operations and processes.
Job DescriptionThis role requires a highly motivated and driven individual to join our Quantitative, Translational & ADME Sciences (QTAS) team. The successful candidate will have a substantial background in data and computer science with an emphasis on supporting, developing, and implementing IT solutions for lab-based systems as well as utilizing computational methods.
The ideal candidate should possess a deep knowledge in AI/ML, with a focus on both supervised and unsupervised learning techniques. They must be adept at applying these methods to large datasets for predictive modeling; in this context- drug properties and discovery patterns in ADME datasets.
The role requires effective collaboration with interdisciplinary teams to integrate AI insights into drug development processes. Strong communication skills are necessary to convey complex AI/ML concepts to a diverse audience.
Key Responsibilities:
- Provide business-centric support of IT systems and platforms in support of our scientific operations and processes.
- Develop, implement, troubleshoot, and support solutions independently for the digital infrastructure and workflows within QTAS including custom platform/coding solutions, visualization tools, integration of new software/hardware, and analysis and troubleshooting support.
- Lead the analysis of large ADME-related datasets, contributing to the understanding and optimization of drug absorption, distribution, metabolism, and excretion properties.
- Apply computational tools and machine learning/deep learning techniques to analyze and interpret complex biological data relevant to drug discovery.
- Develop predictive models and algorithms for identifying potential drug candidates with desirable ADME properties.
- Collaborate with teams across biological sciences and drug discovery to integrate computational insights into practical drug development strategies.
- Communicate findings and strategic input to cross-functional teams, including Translational Science, Medicine, and Late Development groups.
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