The Senior AI/ML Data Scientist – Natural Language Processing (NLP) role involves helping to develop and deploy production-grade NLP products for unstructured and semi-structured data from across our company’s research and development pipeline. These models and workflows will help solve real-world problems and contribute to Artificial Intelligence and Machine Learning (AI/ML) in therapeutic research and development. Key focus areas will include the scalable deployment of ML and Generative AI approaches (such as Large Language Models, or LLMs) for surfacing insights from proprietary unstructured research data and biomedical literature, as well as developing fit-for-purpose approaches for the likes of text classification, relation extraction, and entity linking. The position is embedded in a cross-disciplinary team of data scientists, bioinformaticians, and engineers that are all focused on using cutting-edge software, AI/ML, and data science techniques to drive drug discovery and development.
The following are preferred skills and experience, not strict requirements: * Fluency in Python programming, version control and collaboration with git, environment management (e.g., poetry, conda, docker), standard Python packages (e.g., pandas, numpy, matplotlib), and at least one ML framework (e.g., pytorch, tensorflow, fairseq) * Experience with scalable data engineering frameworks such as Apache Spark and orchestration frameworks such as Airflow, and/or experience with semantic search and retrieval frameworks (e.g., development and benchmarking of embedding models and retrieval approaches in the context of Retrieval Augmented Generation, RAG) * Experience with ML model deployment and operations (e.g., DevOps, MLOps, LLMOps), including CI/CD workflows and tooling (e.g., Github actions) * Experience with standard operations on non-relational (e.g., Elasticsearch/Opensearch, MongoDB, Neptune), relational databases (e.g., PostgreSQL), and vector databases (e.g., pgvector, Elasticsearch dense vectors) and deployment of APIs and web applications (e.g., flask, fastAPI, django, or dash) * Working knowledge of statistical learning, such as supervised, unsupervised, and weakly supervised learning, particularly in NLP contexts * Working knowledge of NLP and/or Generative AI libraries (e.g., regular expressions, spacy, langchain), text annotation tools, and/or semantic frameworks (e.g. RDF triplestores, property graphs, ontology management) * A demonstrated ability to engage cross-functional teams and stakeholders, including an eagerness to acquire a level of domain knowledge
The types of datasets we focus on are both internal (e.g., electronic lab notebooks, safety reports, regulatory documents, clinical results) and external (e.g., public literature and Electronic Medical Records). In addition to new tool development, we often consult with some of our 5,000+ stakeholders (scientists, engineers, regulatory liaisons, data scientists, etc.) on their own projects, as well as additional stakeholders from across our multi-national company. We strive to enhance data science, NLP, and AI literacy across these groups. As part of our work, we have opportunities to coauthor presentations, reports, manuscripts, and/or public code releases.
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Expected salary range: $122,800.00 - $193,300.00 Available benefits include bonus eligibility, long term incentive if applicable, health care and other insurance benefits (for employee and family), retirement benefits, paid holidays, vacation, and sick days. A summary of benefits is listed here.
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