Are you excited to solve complex data science problems using NLP, machine learning, and large-scale data?
Do you enjoy collaborating with others to build impactful data products that power real-world applications?
About our Team
LexisNexis Legal & Professional, which serves customers in more than 150 countries with 11,800 employees worldwide, is part of RELX (http://www.relx.com), a global provider of information-based analytics and decision tools for professional and business customers. Our company has been a long-time leader in deploying AI and advanced technologies to the legal market to improve productivity and transform the overall business and practice of law, deploying ethical and powerful generative AI solutions with a flexible, multi-model approach that prioritizes using the best model from today’s top model creators for each individual legal use case. The company employs over 2,000 technologists, data scientists, and experts to develop, test, and validate solutions in line with RELX Responsible AI Principles (https://stories.relx.com/responsible-ai-principles/index.html).
About the Yoda Team
The Yoda team is a small, focused division within LexisNexis responsible for managing core datasets related to people, organizations, and taxonomies. These datasets are published internally and used by teams across the company to build products and deliver customer value.
We are looking for a Data Scientist to join our team and help advance our work in data extraction, data structuring, classification, and analysis. This role is ideal for someone who is versatile, collaborative, and excited to solve complex problems using NLP, machine learning, large language models, regression, classification, and information retrieval techniques.
Responsibilities
As a Senior Data Scientist II on the Yoda team, you will:
- 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.
Requirements:
- 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 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 such as EC2 and Lambda.
- At least 5 years of recent coding experience using Python and/or Java or Scala.
- SQL programming experience.
- Experience designing, working with, and reasoning 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, implement, and achieve business objectives and goals.
- Ability to work effectively on a small team and provide technical leadership or mentorship to junior team members.
Preferred Qualifications:
- Experience with large language models and generative AI workflows.
- Experience with entity extraction, taxonomy management, knowledge graphs, or data enrichment.
- Experience working with large-scale legal, news, financial, business, or professional data.
- Familiarity with model evaluation, experimentation frameworks, MLOps practices, and production of ML monitoring.
- Ability to quickly evaluate new approaches and determine the right tool or model for a given business problem.
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 the Business
LexisNexis Legal & Professional® provides legal, regulatory, and business information and analytics that help customers increase their productivity, improve decision-making, achieve better outcomes, and advance the rule of law around the world. As a digital pioneer, the company was the first to bring legal and business information online with its Lexis® and Nexis® services.
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.
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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.
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Skills Required
- 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, including scikit-learn, pandas, and NumPy
- Experience with NLP tools and methods such as OpenNLP, Stanford NLP, LDA, Gensim, or spaCy
- Proficiency training large-scale models with at least one deep learning framework such as TensorFlow, Keras, PyTorch, MXNet, Caffe, or Caffe2
- Experience building and deploying cloud-based services, preferably using AWS EC2 and Lambda
- At least 5 years of recent coding experience using Python, 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
- Ability to set, communicate, implement, and achieve business objectives and goals
- Ability to work effectively on a small team and provide technical leadership or mentorship to junior team members
- Experience with large language models and generative AI workflows
- Experience with entity extraction, taxonomy management, knowledge graphs, or data enrichment
- Experience working with large-scale legal, news, financial, business, or professional data
- Familiarity with model evaluation, experimentation frameworks, MLOps practices, and production ML monitoring
- Ability to quickly evaluate new approaches and select the right tool or model for a business problem
LexisNexis Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about LexisNexis and has not been reviewed or approved by LexisNexis.
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Healthcare Strength — Healthcare options are often described as comprehensive, spanning medical, dental, and vision coverage alongside life and disability protection. Wellbeing programming such as wellness initiatives and fitness support is also positioned as part of the overall package.
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Retirement Support — Retirement benefits are repeatedly framed as a meaningful component of total rewards through 401(k) matching and access to stock purchase opportunities. Performance bonuses and charitable matching are also included as financial-support features within the broader rewards mix.
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Leave & Time Off Breadth — Time-off offerings are portrayed as broad, including PTO, paid holidays, sick leave, and paid volunteer time. Flexible work arrangements, including remote options and flexible hours, further strengthen the overall rewards experience.
LexisNexis Insights
What We Do
LexisNexis Legal & Professional is a leading global provider of legal, regulatory and business information and analytics that help customers increase productivity, improve decision-making and outcomes, and advance the rule of law around the world. We help lawyers win cases, manage their work more efficiently, serve their clients better and grow their practices. We assist corporations in better understanding their markets, monitoring their brands and competition, and in mitigating business risk. We collaborate with universities to educate students, and we support nation-building with governments and courts by making laws accessible and strengthening legal infrastructures. We partner with leading global associations and customers to collect evidence against war criminals and provide tools to combat human trafficking. LexisNexis Legal & Professional, which serves customers in more than 130 countries with 10,000 employees worldwide, is part of RELX Group, a global provider of information and analytics for professional and business customers across industries.
