
10,000+ employees
Founded 1970
âïž Legal
đŒ Consulting
đ„ Healthcare
đ° Corporate Round on 2021-06
Legal âą Consulting âą Healthcare
LexisNexis is a provider of professional solutions tailored for law firms, corporations, government agencies, and academic institutions. It offers legal solutions, news, and business insights. LexisNexis also provides risk solutions for companies and government agencies, focusing on data analytics for compliance, customer acquisition, fraud detection, health outcomes, identity solutions, investigations, receivables management, risk decisioning, and workflow optimization. As part of the RELX Group, LexisNexis is committed to enhancing digital experience through data and analytics.
đ„ 1 minute ago
đïž District of Columbia, Florida, +2 more states â Remote
đ” $110.1k - $183.5k / year
â° Full Time
đ Senior
đ Data Scientist
đŠ H1B Visa Sponsor
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10,000+ employees
Founded 1970
âïž Legal
đŒ Consulting
đ„ Healthcare
đ° Corporate Round on 2021-06
Legal âą Consulting âą Healthcare
LexisNexis is a provider of professional solutions tailored for law firms, corporations, government agencies, and academic institutions. It offers legal solutions, news, and business insights. LexisNexis also provides risk solutions for companies and government agencies, focusing on data analytics for compliance, customer acquisition, fraud detection, health outcomes, identity solutions, investigations, receivables management, risk decisioning, and workflow optimization. As part of the RELX Group, LexisNexis is committed to enhancing digital experience through data and analytics.
âą Solve challenging problems in natural language processing, machine learning, and information retrieval, including topical classification, sentiment analysis, entity extraction, and user intent detection âą Research, build, train, evaluate, and deploy machine learning models using traditional and deep learning techniques âą Develop robust NLP-based models over large-scale news, financial, legal, and business corpora âą Design and improve scalable NLP and machine learning pipelines âą Evaluate state-of-the-art algorithms, models, APIs, and open-source tools, including BERT, ELMo, and GPT-based models âą Translate complex business requirements into actionable technical stories with practical estimates âą Partner with product leaders, engineers, and cross-functional stakeholders to apply data science solutions to business problems âą Contribute to best practices for model development, evaluation, deployment, monitoring, and maintenance âą Support and mentor junior team members while contributing to a small, collaborative team
âą Strong understanding of machine learning techniques, including classification, clustering, recommendation systems, regression, and statistical modeling âą Hands-on experience with Python machine learning and data science libraries such as scikit-learn, pandas, NumPy, and related tools âą Experience with NLP tools and methods such as OpenNLP, Stanford NLP, LDA, Gensim, spaCy, or similar frameworks âą Proficiency training large-scale models using at least one modern deep learning framework such as TensorFlow, Keras, PyTorch, MXNet, Caffe, or Caffe2 âą Experience building and deploying cloud-based services, preferably using AWS services such as EC2 and Lambda âą At least 5 years of recent coding experience using Python and/or Java or Scala âą SQL programming experience âą Experience designing, working with, and reasoning about complex data models âą Familiarity with cloud-based machine learning environments, Spark, visualization and dashboarding tools, Elasticsearch, Solr, and graph databases such as JanusGraph or Neptune âą Ability to set, communicate, implement, and achieve business objectives and goals âą Ability to work effectively on a small team and provide technical leadership or mentorship to junior team members âą Experience with large language models and generative AI workflows âą Experience with entity extraction, taxonomy management, knowledge graphs, or data enrichment âą Experience working with large-scale legal, news, financial, business, or professional data âą Familiarity with model evaluation, experimentation frameworks, MLOps practices, and production ML monitoring
âą Annual incentive bonus eligibility âą Flexible working hours âą Wellbeing initiatives âą Shared parental leave âą Study assistance âą Sabbaticals âą Country-specific benefits âą Accommodation or adjustment support during hiring for disabilities or other needs
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