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.

Qualifications:

• Bachelor’s or Master’s Degree in Data Science, Computer Science, Computational Chemistry, or related relevant discipline typically with 5 to 10 (BS) or 2 to 5 (MS) years related industry experience.
• Passion for data analysis, solving technical problems and applying new technologies to further scientific goals.
• Strong proficiency in programming (e.g., SQL, Python, R, MATLAB), database technologies (Oracle, mySQL, relational databases; graph databases are a plus), machine learning/deep learning (network architectures are a plus), dimensionality reduction techniques (e.g., PCA), and possible cheminformatics software suites
• Demonstrated experience in the analysis and visualization of large datasets. Proficiency in any of the following technologies is valued: Python (including libraries such as Matplotlib, Seaborn, Plotly, Bokeh), JavaScript, Julia, Java/Scala, or R (including Shiny).
• Comfortable working in cloud and high-performance computational environments (e.g., AWS and Oracle Cloud)
• Excellent communication skills and ability to work effectively in interdisciplinary teams.
• Understanding of pharma R&D process and challenges in drug discovery is preferred.
• Proven ability to work in a team environment; ability to work well in a collaborative fast-paced team environment.
• Excellent oral and written communication skills and the ability to convey IT related notions to cross-disciplinary scientists.
• Thorough theoretical and practical understanding of own scientific discipline
• Background and/or experience in the biotechnology, pharmaceutical, biology, or chemistry fields is preferred.

Top 3-5 skills:

• Experience with programming and/or other technologies; e.g. SQL, Python (including Matplotlib, Seaborn, Plotly, Bokeh), R (including Shiny), Javascript, Java/Scala, MATLAB, etc.
• Knowledge in Artificial Intelligence/Machine Learning (AI/ML)
• Degree in Data Science, Computer Science, Computational Chemistry or related field (BS 5+ yrs, MS 2-5 years)
• Strong proficiency in database technologies (Oracle, mySQL, relational databases; graph databases are a plus)

Key Leadership Competencies:

• Builds strong relationships with peers and cross-functionally with partners outside of team to enable higher performance.
• Learns fast, grasps the "essence" and can change course quickly where indicated.
• Raises the bar and is never satisfied with the status quo.
• Creates a learning environment, open to suggestions and experimentation for improvement.
• Embraces the ideas of others, nurtures innovation and manages innovation to reality.