Senior Data Scientist II

RELXRELX·Remote(United States)
Data & Analytics
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WFA Digital Insight

As the demand for AI and data science specialists continues to surge, with a notable 27% increase in job postings over the past year, professionals with expertise in natural language processing and machine learning are in high demand. RELX, a leader in information-based analytics, stands out for its commitment to ethical AI solutions and its ongoing investments in cutting-edge technologies. Candidates interested in this Senior Data Scientist II role should be prepared to leverage their skills in machine learning, NLP, and data analysis to drive impactful solutions. With the remote job market offering more flexibility than ever, it's essential for applicants to demonstrate not only technical prowess but also the ability to collaborate effectively in a distributed team environment.

Job Description

About the Role

The Senior Data Scientist II position at RELX is a unique opportunity for a skilled professional to join the Yoda team, a specialized division within LexisNexis Legal & Professional. This role involves working closely with a small, focused team responsible for managing core datasets related to people, organizations, and taxonomies. These datasets are crucial for internal product development and customer value delivery across the company. The ideal candidate will be versatile, collaborative, and excited about solving complex problems using NLP, machine learning, and large language models.

The Yoda team's work has a direct impact on the development of innovative products and services that transform the legal market. By advancing data extraction, structuring, classification, and analysis, the team contributes to ethical and powerful generative AI solutions. RELX's commitment to responsible AI principles ensures that all solutions are developed and deployed with the highest ethical standards in mind.

What You Will Do

  • Solve challenging problems in natural language processing, machine learning, and information retrieval, including topical classification, sentiment analysis, entity extraction, and user intent detection.
  • Research, build, train, evaluate, and deploy machine learning models using both traditional and deep learning techniques.
  • Develop robust NLP-based models over large-scale corpora, including news, financial, legal, and business data.
  • Design and improve scalable NLP and machine learning pipelines.
  • Evaluate state-of-the-art algorithms, models, APIs, and open-source tools, including BERT, ELMo, GPT-based models, and related technologies.
  • Translate complex business requirements into actionable technical stories with practical estimates.
  • Partner with product leaders, engineers, and cross-functional stakeholders to apply data science solutions to real business problems.
  • Contribute to best practices for model development, evaluation, deployment, monitoring, and maintenance.
  • Support and mentor junior team members while contributing as part of a small, collaborative team.
  • Collaborate in the design and implementation of cloud-based services, preferably using AWS services such as EC2 and Lambda.

What We Are Looking For

  • Strong understanding of machine learning techniques, including classification, clustering, recommendation systems, regression, and statistical modeling.
  • Hands-on experience with Python machine learning and data science libraries such as scikit-learn, pandas, NumPy, and related tools.
  • Experience with NLP tools and methods such as OpenNLP, Stanford NLP, LDA, Gensim, spaCy, or similar frameworks.
  • Proficiency in training large-scale models using at least one modern deep learning framework such as TensorFlow, Keras, PyTorch, MXNet, Caffe, or Caffe2.
  • Experience building and deploying cloud-based services, preferably using AWS services.
  • At least 5 years of recent coding experience using Python and/or Java or Scala.
  • SQL programming experience.
  • Experience designing, working with, and reasoning about complex data models.
  • Familiarity with cloud-based machine learning environments, Spark, visualization and dashboarding tools, Elasticsearch, Solr, and graph databases such as JanusGraph, Neptune, or similar technologies.
  • Strong ability to set, communicate, and manage priorities.

Nice to Have

  • Experience with containerization using Docker.
  • Knowledge of agile development methodologies.
  • Participation in open-source projects or personal projects related to NLP and machine learning.
  • Certification in data science or a related field.
  • Experience with DevOps practices and tools.

Benefits and Perks

  • Competitive salary package.
  • Opportunity to work with a global leader in information-based analytics.
  • Collaborative and dynamic work environment.
  • Flexible working arrangements, including remote work options.
  • Access to cutting-edge technologies and tools.
  • Professional development opportunities, including training and conference attendance.
  • Comprehensive health insurance and wellness programs.
  • Generous paid time off and holiday package.
  • Remote stipend for home office setup and ongoing support.

How to Stand Out

  • Build a strong portfolio: Showcase your experience with NLP and machine learning projects, including any personal projects or contributions to open-source frameworks.
  • Stay updated with industry trends: Follow leading researchers and institutions in the field of NLP and machine learning to stay informed about the latest developments and advancements.
  • Prepare for technical interviews: Review common machine learning and NLP interview questions and practice coding challenges to improve your problem-solving skills under time pressure.
  • Highlight collaboration skills: Emphasize your ability to work effectively in a team environment and communicate complex technical ideas to non-technical stakeholders.
  • Negotiate based on market standards: Research the current market rates for data scientist positions in your area to negotiate a fair salary.
  • Ask about company culture: During interviews, inquire about the company's approach to remote work, team dynamics, and opportunities for growth and professional development.
  • Be prepared to discuss ethical considerations: Show awareness of the ethical implications of AI and data science solutions and be ready to discuss how you would approach these considerations in your work.

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