Senior Specialist, Data Science

Job Description

We are seeking an exceptional and highly motivated informatician to join the Cheminformatics group within Modeling and Informatics (M&I) at our Boston/Cambridge, MA. This role requires strong interpersonal and problem-solving skills and experience working in a cross-functional team environment. It involves both the development of innovative computational methods involving AI/ML and cheminformatics, as well as direct application of advanced computational approaches to the invention of novel medicines.

M&I is a diverse and inclusive team within the Research Laboratories Discovery Chemistry organization, comprising approximately 60 computational chemists, cheminformaticians, and data scientists. We leverage cutting-edge capabilities in structure-based modeling, predictive science, and AI/ML to drive drug design and development globally, with a proven track record of pipeline impact. The selected candidate will work closely with the M&I team, our world-class chemistry teams, as well cross-functionally with experimental and computational colleagues in the early target discovery space on innovative science that has a wealth of opportunities to impact drug discovery and ultimately save and improve patient lives.
 

Key responsibilities will include:

• Implement and apply effective AI/ML, cheminformatics, and bioinformatics workflows to impact early target discovery.

• Leverage novel ML, statistics, and informatics techniques to improve tool compound selection, library design, hit identification, and target prioritization

• Analyze, interpret, and summarize complex chemical biology and high throughput biology data and utilize a variety of data visualization tools to communicate findings.

• Analyze and integrate internal and external knowledge to facilitate biological and chemical signature identification and enable biomarker discovery.

• Deliver optimized informatics algorithms and workflows to expedite data analysis pipelines in the early target discovery space for small molecules and other modalities.

• Continue research in areas of AI/ML and cheminformatics relevant to drug discovery, and evaluate new technology 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.

• Proactively engage with cross-functional teams of experimental and computational scientists and collaborate effectively to advance project and pipeline goals

Position Qualifications:

Education:

• Bachelor's (with 7 years), Master's (with 4 years) or Ph.D. in cheminformatics, bioinformatics, computational chemistry, computational biology, chemical engineering, or related fields and relevant experience listed below

Required Experience and Skills:

• Experience applying cheminformatics, bioinformatics or AI/ML approaches to problem-solving in drug discovery.

• Broad understanding of modern data science methods, particularly machine learning, e.g., predictive modeling, 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, cheminformatics and bioinformatics toolkits.

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 image-based screening data analysis methods.

• Experience in chemical and biological signature identification and/or biomarker discovery.

• Experience working in multidisciplinary teams that include experimental scientists.

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