Data Scientist II

Posted Yesterday
Be an Early Applicant
2 Locations
In-Office
Mid level
Artificial Intelligence • Healthtech • Information Technology • Other • Analytics
The Role
Design and build ML, NLP, and generative AI systems for scientific discovery and knowledge extraction. Work with large heterogeneous scientific datasets to develop semantic search, entity extraction, QA, summarization, embeddings, and production-ready models. Implement model evaluation, fine-tuning, deployment, monitoring, drift detection, and scalable data pipelines while collaborating across engineering, product, UX, and research teams.
Summary Generated by Built In

Data Scientist

AI for Science, Research Intelligence & Knowledge Discovery

Technology – Data Science Organization

Are you excited by the opportunity to use machine learning, NLP, and generative AI to help researchers discover knowledge faster and make better decisions?

Would you enjoy turning complex scientific and business challenges into practical, production-ready AI solutions that create real user value?

About our Team

Our global team support products education electronic health records that introduce students to digital charting and prepare them to document care in today’s modern clinical environment. We have a very stable product that we’ve worked to get to and strive to maintain. Our team values trust, respect, collaboration, agility, and quality.

About the Role

In this role, you will design and build machine learning, NLP, and generative AI solutions that support scientific discovery, knowledge extraction, decision support, and intelligent content understanding. You will work with large-scale scientific content and data, applying the right techniques to solve complex problems and deliver reliable, production-ready systems. Working closely with cross-functional partners, you will help turn ambiguous challenges into measurable outcomes that improve how researchers discover and use knowledge.

Responsibilities

  • Design and build machine learning, NLP, and generative AI systems for scientific discovery, knowledge extraction, decision support, and intelligent content understanding.

  • Work with large-scale, complex, and heterogeneous data, including scientific publications, research datasets, knowledge graphs, ontologies, taxonomies, citations, metadata, and content from every scientific discipline.

  • Apply the right technique to each problem, using approaches such as classification, regression, clustering, ranking, feature engineering, deep learning, embeddings, LLMs, retrieval, and generative AI.

  • Develop capabilities for semantic search, information retrieval, entity extraction, content classification, recommendation, ranking, summarization, question answering, and evidence-grounded generation.

  • Build, evaluate, fine-tune, prompt, and integrate models into robust production systems, while continuously improving quality, relevance, reliability, and user value.

  • Write clean, tested, production-quality Python and contribute reusable data science components, packages, and scalable data pipelines for preprocessing, inference, experimentation, monitoring, and continuous improvement.

  • Support deployment, monitoring, model maintenance, drift detection, automated retraining, and ongoing optimization of data science systems.

  • Collaborate with engineering, product, UX, analytics, research, and domain experts, and communicate technical concepts, model behavior, insights, trade-offs, and recommendations clearly to technical and non-technical audiences.

Requirements

  • Experience in data science, machine learning, artificial intelligence, NLP, statistics, applied mathematics, computer science, or a related quantitative area.

  • Experience working with frontier LLMs such as OpenAI’s GPTs, Anthropic’s Claude, and Google’s Gemini, including fine-tuning LLMs and/or SLMs.

  • Strong Python skills and a habit of writing clean, maintainable, well-tested code.

  • A solid grasp of machine learning fundamentals, including supervised and unsupervised learning, feature engineering, model evaluation, model selection, and performance measurement.

  • Experience working with structured, semi-structured, or unstructured data, especially large-scale text or content datasets.

  • Familiarity with common data science and machine learning tools such as Pandas, NumPy, SciPy, Scikit-learn, PyTorch, TensorFlow, or Matplotlib.

  • The ability to translate complex and ambiguous requirements into practical, measurable, data-driven solutions, with strong analytical thinking, problem-solving skills, and attention to quality.

  • Clear communication skills, a collaborative approach to working with engineering, product, and business stakeholders, and a genuine interest in building production-ready systems that deliver real user value.

Work in a Way That Works for You

We promote a healthy work/life balance across the organisation. We offer an appealing working prospect for our people. With numerous wellbeing initiatives, shared parental leave, study assistance, and sabbaticals, we will help you meet your immediate responsibilities and your long-term goals.

Working Pattern

Working flexible hours - flexing the times when you work in the day to help you fit everything in and work when you are the most productive

About Elsevier

Elsevier is a global leader in information and analytics. We help researchers and healthcare professionals advance science and improve health outcomes for the benefit of society.

Building on our publishing heritage, we combine quality information, vast datasets, advanced analytics, and innovative technologies to support visionary science and research, health education, interactive learning, and exceptional healthcare and clinical practice.

At Elsevier, your work contributes to the world’s grand challenges and a more sustainable future. We harness technology to support science and healthcare in partnership with the communities we serve.

Together, we create possibilities. Join us.

We know your well-being and happiness are key to a long and successful career. We are delighted to offer country specific benefits. Click here to access benefits specific to your location.

We are committed to providing a fair and accessible hiring process. If you have a disability or other need that requires accommodation or adjustment, please let us know by completing our Applicant Request Support Form or please contact 1-855-833-5120.

Criminals may pose as recruiters asking for money or personal information. We never request money or banking details from job applicants. Learn more about spotting and avoiding scams here.

Please read our Candidate Privacy Policy.

We are an equal opportunity employer: qualified applicants are considered for and treated during employment without regard to race, color, creed, religion, sex, national origin, citizenship status, disability status, protected veteran status, age, marital status, sexual orientation, gender identity, genetic information, or any other characteristic protected by law.

USA Job Seekers:

EEO Know Your Rights.

Skills Required

  • Experience in data science, machine learning, AI, NLP, statistics, applied math, or related quantitative area
  • Experience working with frontier LLMs (OpenAI GPTs, Anthropic Claude, Google Gemini) including fine-tuning
  • Strong Python skills; ability to write clean, maintainable, well-tested code
  • Solid grasp of ML fundamentals (supervised/unsupervised learning, feature engineering, model evaluation, model selection)
  • Experience with large-scale structured, semi-structured, or unstructured text/content datasets
  • Familiarity with data science tools: Pandas, NumPy, SciPy, scikit-learn, PyTorch, TensorFlow, Matplotlib
  • Experience building semantic search, retrieval, embeddings, ranking, recommendation, summarization, QA, and evidence-grounded generation
  • Experience deploying and maintaining production ML systems, including monitoring, drift detection, and automated retraining
  • Strong analytical problem-solving, ability to translate ambiguous requirements, and clear communication with cross-functional stakeholders
Am I A Good Fit?
beta
Get Personalized Job Insights.
Our AI-powered fit analysis compares your resume with a job listing so you know if your skills & experience align.

The Company
0 Employees
Year Founded: 1880

What We Do

Elsevier is a world-leading provider of information solutions that enhance the performance of science, health, and technology professionals, empowering them to make better decisions, and deliver better care. Because informed decisions lead to better outcomes, Elsevier is a leader in information and analytics for customers across the global research and health ecosystems. Elsevier helps researchers and healthcare professionals advance science and improve health outcomes for the benefit of society. We do this by facilitating insights and critical decision-making for customers across the global research and health ecosystems.

Similar Jobs

Elsevier Logo Elsevier

Senior Data Scientist

Artificial Intelligence • Healthtech • Information Technology • Other • Analytics
In-Office
2 Locations

Multiverse Logo Multiverse

Senior Data Scientist

Artificial Intelligence • Edtech • Information Technology
Hybrid
London, Greater London, England, GBR
800 Employees
In-Office
3 Locations
2722 Employees
Hybrid
2 Locations
9574 Employees
8-8 Annually

Similar Companies Hiring

Hanover Park Thumbnail
Artificial Intelligence • Fintech • Software • Financial Services
New York, New York
31 Employees
Golden Pet Brands Thumbnail
Digital Media • eCommerce • Information Technology • Marketing Tech • Pet • Retail • Social Media
El Segundo, California
178 Employees
Onshore Thumbnail
Artificial Intelligence • Fintech • Software • Financial Services
New York, New York
60 Employees

Sign up now Access later

Create Free Account

Please log in or sign up to report this job.

Create Free Account