Senior Data Scientist I

Posted 3 Days Ago
Be an Early Applicant
2 Locations
In-Office
54K-90K Annually
Senior level
Artificial Intelligence • Healthtech • Information Technology • Other • Analytics
The Role
Lead development and productionization of GenAI, NLP, and RAG solutions for life-sciences products. Build production-ready Python packages, preprocess large multilingual data, design and evaluate transformer/agentic models, integrate with engineering teams, monitor model quality and drift, and mentor junior data scientists.
Summary Generated by Built In

Are you interested in working with data and analytics to solve problems?


Are you interested in bringing your GenAI, ML and NLP expertise to projects?


About our Team

Data Science Life Sciences is a diverse team focusing on GenAI, ML, NLP. We mainly develop best-in-class enrichment pipelines for Elsevier’s life science .com products such as Reaxys, Embase and Pharmapendium.

About the Role

As a Senior Data Scientist, you will play a pivotal role in the development and deployment of cutting-edge Gen AI models and solutions. You will be responsible for building, testing, and maintaining our Gen AI, RAG and NLP solutions

You will work throughout the whole life cycle of data science projects: design, implementation, production and beyond. You will deliver efficient and production-ready Python code. You will collaborate closely with developers to deploy and productionize our data science pipelines and with subject matter experts in biology and chemistry domains to validate the output.

This role requires a strong foundation in Natural Language Processing (NLP), Machine Learning, Transformer models and Generative AI, as well as proficiency in Python.

Responsibilities

  • Data collection, data analysis, model development, defining quality metrics, quality assessment of models and regular presentations to stakeholders.
  • Creating production-ready Python packages for each component of data science pipelines (such as pre-processing and model inference) and their deployment together with software engineering team
  • Optimizing and customizing Retrieval Augmented Generation (RAG) pipelines to meet specific project requirements that involve content ingestion, machine translation, and contextualized information retrieval
  • Ingesting, preprocessing, and transforming large-scale multilingual data to ensure high-quality inputs for downstream models.
  • Building AI agentic models integrated with RAG pipelines.
  • Conducting rigorous testing and evaluation of AI models to ensure high performance and reliability.
  • Integrating data science components and performing end-to-end quality assessments.
  • Maintaining robustness of data science pipelines against model drift and ensuring consistent output quality.
  • Establishing reporting processes for pipeline performance and developing automated re-training strategies for existing pipelines.
  • Collaborating with cross-functional teams to integrate AI solutions into existing products and services.
  • Leading and managing projects with a team of data scientists and independently executing the entire small-scale projects
  • Mentoring junior data scientists and fostering a knowledge-sharing culture within the team.
  • Staying up-to-date with the latest advancements in AI, machine learning, and NLP technologies.

Requirements


  • Master’s or Ph.D. in Computer Science, Data Science, Artificial Intelligence, or a related field.
  • 5+ years of relevant applied experience in data science, with a focus on Generative AI, NLP, and machine learning.
  • Proficiency in Python for data analysis, model development, and deployment.
  • Strong experience with transformer models
  • Proficiency in Generative AI technologies, including utilizing LLMs via API access, LLM evaluation tools, and prompt engineering.
  • Knowledge of various RAG pipelines and their practical implementation.
  • Experience building Agentic RAG systems is strong requirement.
  • Experience with AI agent management frameworks such as LangChain, or similar tools.
  • Experience with advanced algorithms in deep learning, neural networks, reinforcement learning, and transfer learning.
  • Familiarity with traditional machine learning algorithms such as random forests, SVM, logistic regression, and Bayesian modelling for model building, validation, and testing.
  • Familiarity with cloud platforms (e.g., Bedrock, AWS, Azure) for model deployment and the creation of production-ready pipelines.
  • Proficiency in data visualization tools and techniques.
  • Experience with version control systems (e.g., GitLab or GitHub), Jira, and working in an Agile environment.
  • Proficient in using OpenSearch and Databricks.
  • Excellent problem-solving and analytical skills, with strong attention to detail.
  • Strong communication skills and the ability to work effectively in a team-oriented environment.

Work in a way that works for you

We promote a healthy work/life balance across the organization. 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. 

  • Flexible working 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 the business

As 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 and vast data sets with analytics to support visionary science and research, health education, and interactive learning, as well as exceptional healthcare and clinical practice. At Elsevier, your work contributes to the world’s grand challenges and a more sustainable future. We harness innovative technologies to support science and healthcare to partner for a better world.

Primary Location Base Pay Range: NLD Amsterdam (Radarweg) €53,800 - €89,900. This role is covered by the Collective Labor Agreement Publishing Industry.

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

  • Master's or Ph.D. in Computer Science, Data Science, Artificial Intelligence, or related field.
  • 5+ years of applied experience in data science with focus on Generative AI, NLP, and machine learning.
  • Proficiency in Python for data analysis, model development, and deployment.
  • Strong experience with transformer models.
  • Proficiency with Generative AI technologies, including using LLMs via APIs and LLM evaluation tools.
  • Knowledge and practical implementation experience with Retrieval Augmented Generation (RAG) pipelines.
  • Experience building Agentic RAG systems (strong requirement).
  • Experience with AI agent management frameworks such as LangChain or similar tools.
  • Experience with advanced deep learning algorithms, neural networks, reinforcement learning, and transfer learning.
  • Familiarity with traditional ML algorithms (random forests, SVM, logistic regression, Bayesian modelling) for model building and validation.
  • Familiarity with cloud platforms for model deployment and production pipelines (e.g., Amazon Bedrock, AWS, Azure).
  • Proficiency in data visualization tools and techniques.
  • Experience with version control systems (GitLab or GitHub), Jira, and working in an Agile environment.
  • Proficient in using OpenSearch and Databricks.
  • Excellent problem-solving, analytical, communication skills, and ability to work in a team-oriented environment.
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The Company
HQ: Amsterdam
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.

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