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Senior Data Scientist II

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LexisNexis

10,000+ employees

Founded 1970

⚖ Legal

đŸ’Œ Consulting

đŸ„ Healthcare

💰 Corporate Round on 2021-06

Legal ‱ Consulting ‱ 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.

📋 Description

‱ 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 traditional and deep learning techniques ‱ Develop robust NLP-based models over large-scale news, financial, legal, and business corpora ‱ Design and improve scalable NLP and machine learning pipelines ‱ Evaluate state-of-the-art algorithms, models, APIs, and open-source tools, including BERT, ELMo, and GPT-based models ‱ 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 business problems ‱ Contribute to best practices for model development, evaluation, deployment, monitoring, and maintenance ‱ Support and mentor junior team members while contributing to 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 about complex data models ‱ Familiarity with cloud-based machine learning environments, Spark, visualization and dashboarding tools, Elasticsearch, Solr, and graph databases such as JanusGraph or Neptune ‱ 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

đŸ–ïž Benefits

‱ Annual incentive bonus eligibility ‱ Flexible working hours ‱ Wellbeing initiatives ‱ Shared parental leave ‱ Study assistance ‱ Sabbaticals ‱ Country-specific benefits ‱ Accommodation or adjustment support during hiring for disabilities or other needs

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