> Markdown version of [/jobs/ext/2684955-senior-data-scientist-nlp-applied-ai](https://www.wearedevelopers.com/jobs/ext/2684955-senior-data-scientist-nlp-applied-ai). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Data Scientist (NLP & Applied AI) - **Company:** John Wiley & Sons, Inc. - **Location:** Hoboken, NJ, United States - **Experience:** Expert - **Salary:** $109,500.0 - $156,833.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Amazon Web Services, Amazon S3, Encodings, Python (Programming Language), Parquet, Large Language Models, Build Management, Data Lakes - **Published:** September 2, 2026 - **Apply:** https://diversityjobs.com/main/sendform/8/8/28176/1/18165616?backUrl=%2Fcareer%2F18165616%2FSenior-Data-Scientist-Nlp-Applied-Ai-New-Jersey-Hoboken ## About the Role * Strong NLP background across modern (LLMs, transformers, embeddings, retrieval) and classical (NER, classification, sequence labeling) approaches. You've built evaluations and learned from the results. * Clean python. You are comfortable in exploratory notebooks and production repositories, and an engineer taking over a modeling output from you has a good head start. * A habit of comparing approaches and choosing the right one for the task. You can defend "prompt a large LLM" and "train a small classifier on 2,000 labels" with equal seriousness, back the choice with an eval and a cost estimate, and know what to do when performance drifts. Preferred Qualifications: * Experience working with scientific or scholarly text. * Familiarity with AWS (S3, Batch, Lambda, SageMaker) and Parquet or Iceberg data lake patterns. * Experience running LLMs under real cost and latency budgets in production. * Some exposure to agentic AI applications: tool use, multi-step reasoning, guardrails, and evaluation of trajectories rather than single-turn outputs. ## Description We believe in bold ideas, diverse perspectives, and the drive to transform knowledge into impact. Here, your curiosity fuels progress, your voice shapes innovation, and your ambition helps redefine what's possible within science and learning. We are a culture that obsesses over impact, challenges, and drives what's next to power infinite possibilities for our customers, colleagues and society at large., We're building the systems that turn one of the world's largest scientific corpora into research intelligence. That means production NLP pipelines running over millions of journal articles, extracting entities, classifications, claim tuples, and summaries optimized for use by downstream agentic applications. We're looking for a senior data scientist to own domain-specific content modeling work end to end, from the eval set through the pipeline stage that ships it. You'll join a small, senior team where data scientists own their models in production. You'll write the code, own the evaluations, ship the changes, and stay accountable for the outcomes. This is a hands-on role for someone who wants to see their models through to real users in a rapidly evolving market. Job Responsibilities: * Design and build NLP enrichment pipelines that extract entities, classifications, claims, and summaries from scientific full-text at scale. * Compare NLP approaches to extraction and enrichment against LLM-based approaches, and pick the right tool for each task. That means putting traditional NLP (NER, sequence labeling, classification), embedding-based retrieval, LLM prompting, and fine-tuned smaller models on the same table, and defending each choice with evaluation, cost, and operational tradeoffs. This is a core part of the job, not an occasional exercise. * Own evaluation. Build the golden sets in consultation with SMEs and vendors, choose the metrics, and make productive tradeoffs between speed, quality, and cost. * Contribute to agentic AI application work: tool-using systems that reason over the enriched corpus, where your NLP and evaluation background will shape how the agent grounds and defends its answers. * Work directly with editors, product managers, and engineers. Bring the modeling perspective into product decisions, and translate stakeholder pushback into concrete modeling work., We are proud that our workplace promotes continual learning and internal mobility. We offer meeting-free Friday afternoons allowing more time for heads down work and professional development, and through a robust body of employee programing we facilitate a wide range of opportunities to foster community, learn, and grow. ## Related Videos - [A Brief History of Data Storage](https://www.wearedevelopers.com/videos/974-a-brief-history-of-data-storage) - [Parquet, Delta, Iceberg & Ducklake - An introduction for developers](https://www.wearedevelopers.com/videos/100075-parquet-delta-iceberg-ducklake-an-introduction-for-developers) - [WeAreDevelopers LIVE - CSS is DOOMed](https://www.wearedevelopers.com/videos/1838-wearedevelopers-live-css-is-doomed) - [Alibaba Big Data and Machine Learning Technology](https://www.wearedevelopers.com/videos/37-alibaba-big-data-and-machine-learning-technology) - [OLAP for AI Applications and why you should care](https://www.wearedevelopers.com/videos/100212-olap-for-ai-applications-and-why-you-should-care) - [JSON and Beyond](https://www.wearedevelopers.com/videos/968-json-and-beyond) ## Related Articles - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [MLOps – What’s the deal behind it?](https://www.wearedevelopers.com/magazine/125-mlops-what-s-the-deal-behind-it) - [Graph and AI Trends 2026: Why Is AI Running but Not Yet Delivering?](https://www.wearedevelopers.com/magazine/680-graph-and-ai-trends-2026-why-is-ai-running-but-not-yet-delivering) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production)