Senior Data Scientist; NLP
Ann Arbor, Washtenaw County, Michigan, 48113, USA
Listed on 2026-01-12
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IT/Tech
AI Engineer, Machine Learning/ ML Engineer, Data Scientist
Join to apply for the Senior Data Scientist (NLP) role at Clarivate
We are seeking a Senior Data Scientist specializing in Natural Language Processing (NLP) and modern retrieval-augmented generation (RAG) architectures to join our Life Sciences & Healthcare (LS&H) team. This is an amazing opportunity to work on large-scale AI-enabled solutions that modernize and enhance our content delivery systems. You’ll be at the intersection of innovation, architecture, and real-world AI integration. The team consists of several domain and technical experts and reports to the VP of AI, Content.
We would love to speak with you if you have deep expertise across text processing pipelines including indexing, vectorization, prompting, fine‑tuning, summarization and context management and bring hands‑on experience with frameworks like Lang Chain and Lang Graph. Familiarity with architectures such as VRAG and Graph
RAG is highly desirable.
- Bachelor’s degree in Computer Science, Data Science, Computational Linguistics, or a related field
- At least 5 years of hands‑on experience in data science, focused on natural language processing (NLP)
- At least 5 years of experience using Python, with expertise in NLP libraries such as Lang Chain, Lang Graph, or other “Lang”-based toolkits
- Proven experience in model development and applying machine learning techniques to real‑world problems
- Expertise in retrieval‑based LLM workflows (RAG, VRAG, Graph
RAG) - Deep understanding of embedding models, semantic search, and vector stores (e.g., FAISS, Pinecone)
- Experience with document loaders and text splitters/document splitting strategies
- Familiarity with MLOps practices and production‑level deployment of AI pipelines
- Experience with cloud platforms (e.g., AWS, Azure, or GCP)
- Experience applying Graph Neural Networks (GNNs) to retrieval‑enhanced generation
- Knowledge of Lang Smith and vector orchestration platforms
- Familiarity with multilingual NLP and cross‑lingual embeddings
- Exposure to real‑time knowledge graphs and stream‑based RAG systems
- A Master’s or PhD in a technical field (Computer Science, Data Science, etc.)
- Design NLP Workflows:
Develop scalable pipelines for text ingestion, cleaning, normalization, and tokenization to support downstream applications. - Implement Indexing and Vectorization Strategies:
Architect and maintain robust indexing systems and vector databases for semantic search and retrieval. - Develop Prompting and Fine tuning Frameworks:
Create reusable prompting strategies and lead fine‑tuning initiatives for LLMs tailored to business‑specific tasks. - Build Lang Chain/Lang Graph Applications:
Construct dynamic knowledge systems and agentic workflows using Lang Chain and Lang Graph. - Integrate Advanced RAG Architectures:
Apply VRAG and Graph
RAG design patterns to enrich information retrieval and contextual understanding. - Conduct Performance Optimization:
Perform benchmark testing and model evaluations to improve accuracy, efficiency, and scalability of NLP systems. - Collaborate Across Teams:
Work closely with engineering, product, and research stakeholders to deliver integrated AI‑driven features. - Provide Technical Leadership:
Mentor junior data scientists, guide best practices, and drive innovation across AI projects.
This role sits within the Life Sciences & Healthcare (LS&H) segment under the Content Technology team. The team is focused on driving innovation through large‑scale AI solutions. You’ll work closely with the VP of Content Technology, Solutions Architects, and internal stakeholders who are SMEs and the end users of the platform. This role offers the chance to contribute meaningfully to cutting‑edge AI projects that have visibility across leadership teams.
The work is focused, impactful, and offers excellent career advancement opportunities in a fast‑evolving AI space.
- Full‑time permanent position, primarily working core business hours in your time zone, with flexibility to adjust to various global time zones as needed
- Fully remote position based in the US but must reside…
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