Senior Data Specialist, Modeling & Informatics

Key Responsibilities

• Implement and apply effective AI/ML and cheminformatics workflows to impact early target discovery space data analysis.
• Analyze, interpret, and summarize complex chemical biology data and utilize a variety of data visualization tools to communicate findings.
• Deliver optimized informatics algorithms and workflows to expedite drug discovery pipelines in the early target discovery space for small molecules, peptides, and targeted protein degraders.
• Leverage novel ML, statistics, and cheminformatics techniques to improve hit identification for different screening paradigms.
• Analyze and integrate internal and external knowledge to facilitate biological and chemical signature identification.
• Proactively engage with cross-functional teams of experimental and computational scientists and collaborate effectively to advance project and pipeline goals.
• Continue research in areas of AI/ML and cheminformatics relevant to drug discovery, and evaluate new technology and software from commercial sources, open innovation, or external collaborations.
• Effectively communicate scientific results internally and externally through presentations and publications.
• Share AI/ML and/or data engineering knowledge to augment team skills and capabilities.

Qualifications

Education Minimum Requirement: Ph.D. in cheminformatics, bioinformatics, computational biology or chemistry, computer science, statistics or related STEM fields.

Required Experience and Skills

• Experience applying cheminformatics or AI/ML approaches to problem-solving in drug discovery.
• Broad understanding of modern data science methods, particularly machine learning, e.g., predictive modeling, active learning, explainable ML.
• Strong oral and written communication skills, as well as problem-solving skills.
• Track record of scientific publications in peer-reviewed journals.
• Proficiency in scripting (Python and/or R), SQL, and cheminformatics toolkits (OEChem, RDKit, DeepChem).

Preferred Experience and Skills

• Demonstrated ability to develop and apply AI/ML to problems of chemical or biological interest.
• Experience with IT infrastructure such as database systems, cloud computing (such as Databricks, AWS), and high-performance computing in Linux environments.
• Expertise in machine learning libraries (TensorFlow, Keras, PyTorch, Pandas, Scikit-Learn).
• Experience with workflow applications and data analytics software (Pipeline Pilot, Knime, Spotfire).
• Experience with high throughput screening data analysis methods.
• Experience in chemical and biological signature identification and/or biomarker discovery.
• Familiarity with or experience with multiple therapeutic modalities (small molecules, peptides, ADCs, etc.).
• Experience working in multidisciplinary teams that include experimental scientists.