Associate Principal Scientist, Data Science

Job Description

Our Discovery Biologics group is seeking an Associate Principal Scientist with experience in biologics and data science to expand our abilities to design and engineer biotherapeutics.  We are building a department that directly integrates computational and wet-lab researchers with state-of-the-art automation to accelerate the discovery of novel biologics.  We are a highly diverse and collaborative group of biologists, engineers, and computer scientists working at the edge of computation, disease biology, and biotherapeutics.  We collaborate broadly within our Company and with academic and industry partners to accelerate the pace of biologics discovery and engineering.

We recognize that the diversity in our team is our strength, and we are committed to creating an inclusive environment for all employees. Successful candidates must demonstrate inclusive behaviors in working with a diverse group of researchers to drive our core mission.

Job Responsibilities:

In this role, the successful candidate will work side-by-side with wet-lab researchers to design experiments and build datasets that enable machine learning to predict improved biologics.  They will contribute to the identification and application of computational tools that enable the discovery and engineering of biologics.  They will partner broadly across Discovery Biologics, Data Science, and IT to implement systems and practices that support high throughput data capture, integration, and the generation of predictive models.  As part of project teams, they will analyze diverse multidimensional data to enable teams to drive programs forward.  As part of technology development teams, they will pursue novel research that enhances our ability to collect and learn from large datasets.  They will mentor, coach, and train fellow researchers.  The successful candidate will join a diverse group of innovative researchers who are driving the next revolution in biologics discovery and engineering.

• Develop data science based predictive models for biologics to advance early phase drug discovery programs
• Develop computational routines and custom visualizations that enable project teams to impact protein engineering designs and allow teams to rapidly make program decisions from real-time data
• Collaborate across groups to systematize and automate the process of capturing raw instrument data and preparing it for storage and analysis
• Provide technical expertise and leadership for data science working groups and teams
• Author and contribute to presentations, publications, and patents
• Foster a high-performance culture of collaboration, engagement, self-accountability and inclusion

Education:

• Ph.D. (with 4 years of relevant experience) in Computational Biology, Biostatistics, Biochemistry, Computer Science, or a related discipline with demonstrated expertise in biologics and data science, Master’s with (8) years or Bachelor’s with (12) years of relevant experience

Required Experience and Skills:

• Fluency in at least one modern programming language such as C++, Python, or similar
• Strong expertise in data science based predictive models for life science applications
• Experience working with large multidimensional datasets to extract predictive features
• Demonstrated ability to succeed in a collaborative, multidisciplinary team environment
• Excellent written and oral communication skills
• Champion for diverse and inclusive culture
• Mentor and coach group members to complement and strengthen the team

Preferred Experience and Skills:

• Experience with protein engineering or the discovery and development of biologics
• Expertise in the application of relational databases and object-relational databases for semi-structured and unstructured data
• Experience with multiple types of protein structure and sequence representations, featurization, and embeddings
• Experience with protein modeling software (e.g., AlphaFold, Rosetta, TrRosetta, MOE, GROMACs, or similar)
• Familiarity with data visualization tools and libraries
• Ability to teach biologists and biochemists the fundamentals of data science

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Employees working in roles that the Company determines require routine collaboration with external stakeholders, such as customer-facing commercial, or research-based roles, will be expected to comply not only with Company policy but also with policies established by such external stakeholders (for example, a requirement to be vaccinated against COVID-19 in order to access a facility or meet with stakeholders).  Please understand that, as permitted by applicabl