Senior Data Scientist — ML/NLP for AI (Flexible Hours)

Elsevier; Philadelphia (Philadelphia County); On-site; MXN 1,639,000 - 2,730,000; Full time

Benefits offered by this job

Flexible work hours

Wellbeing initiatives

Parental leave

Study assistance

Sabbaticals

Job summary

Elsevier is seeking a Data Scientist to design and deploy ML, NLP, and generative AI solutions for scientific discovery and knowledge extraction. You will work with large-scale scientific content, build production-grade systems, and collaborate across engineering, product, UX, analytics, and research teams to deliver measurable value.

The role emphasizes applying classification, regression, retrieval, and reasoning techniques, and delivering reliable, user-focused AI capabilities in a production

Qualifications

• Experience in data science, ML, AI, NLP, statistics, or related quantitative area.
• Experience with frontier LLMs (GPTs, Claude, Gemini) including fine-tuning.
• Strong Python skills and well-tested, clean code.

Responsibilities

• Design and build ML, NLP, and generative AI systems for research discovery and content understanding.
• Work with large-scale data including publications, datasets, ontologies, and metadata.
• Develop production-ready pipelines for preprocessing, inference, monitoring, and improvement.
• Collaborate with engineering, product, UX, analytics, and domain experts, communicating model behavior and trade-offs clearly.

Skills

Python

NLP

Machine Learning

Analytical thinking

Problem solving

Communication

Tools

Pandas

NumPy

SciPy

Scikit-learn

PyTorch

TensorFlow

Matplotlib

Job description

Elsevier is seeking a Data Scientist to design and deploy ML, NLP, and generative AI solutions for scientific discovery and knowledge extraction. You will work with large-scale scientific content, build production-grade systems, and collaborate across engineering, product, UX, analytics, and research teams to deliver measurable value.

The role emphasizes applying classification, regression, retrieval, and reasoning techniques, and delivering reliable, user-focused AI capabilities in a production