Bayer

Innovation Pipeline Co-Op

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• Contribute technical expertise in a dynamic team environment to advance our initiatives in Natural Language Processing (NLP), protein Language Models (pLM), and genomic Language Models (gLM)
• Perform workflow design, programming, and debugging related to natural language processing (NLP), protein language models, and genomic language models
• Contribute to the development of code, models, and end-to-end workflows for the analysis of text, protein sequences, and genomic data
• Develop accurate and impactful reporting on model inputs, model outputs, observed results, business impact, and key performance indicators
• Present compelling, validated stories to peers, management, and internal customers to drive both strategic and operational changes in business
• Gain experience in model deployment and cloud-based solutions, ensuring effective integration into existing systems.

• Enrolled within a university in the US, pursuing a MS or PhD degree in a relevant field
• Educational preparation or applied experience in at least one of the following areas: Data Science, Natural Language Processing (NLP), Bioinformatics, Genomics, Computer Science, or other related quantitative disciplines
• Demonstrates intermediate proficiency in computational skills and experience building workflows in Python, with familiarity in AWS SageMaker
• Strong proficiency in predictive modeling, including comprehension of theory, modeling/identification strategies, and limitations and pitfalls
• Experience in applying machine learning, deep learning, and other algorithms to text, protein sequences, and genomic data
• Experience in writing and deploying pipelines in a cloud environment
• Ability to deliver valuable analysis through the application of domain knowledge
• Strong communication competencies, including the ability to present and deliver complex quantitative analyses in a clear, concise, and actionable manner to extended teams and small groups of key stakeholders.