> Markdown version of [/jobs/ext/1318681-data-scientist-ii](https://www.wearedevelopers.com/jobs/ext/1318681-data-scientist-ii). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Scientist II - **Company:** LexisNexis - **Location:** Chicago, IL, United States (Remote available) - **Experience:** Expert - **Salary:** $110,100.0 - $183,500.0 - **Contract:** Permanent contract - **Skills:** Mxnet, Java (Programming Language), Application Programming Interfaces (APIs), Amazon Web Services, Amazon Elastic Compute Cloud, Cloud Computing, Computer Programming, Data Cleansing, Elasticsearch, Graph Database, Information Retrieval, Python (Programming Language), Machine Learning, Natural Language Processing, Named Entity Recognition, NumPy, Open Source Technology, Recommender Systems, Cloud Services, Tensorflow, Sentiment Analysis, Apache Solr, SQL Databases, Lexis, Latent Dirichlet Allocation, Pytorch, Large Language Models, Apache Spark, Caffe, Deep Learning, Model Validation, Keras, Pandas, Scikit Learn, Machine Learning Operations, Gensim, Opennlp, Spacy, GPT - **Published:** July 17, 2026 - **Apply:** https://www.dice.com/job-detail/372e6d8e-9df7-4808-a8ef-a33264cec4f1 ## About the Role Do you enjoy collaborating with others to build impactful data products that power real-world applications?, * 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. ## Description 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., 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. ## Related Videos - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) - [Machine learning in the browser with TensorFlowjs](https://www.wearedevelopers.com/videos/155-machine-learning-in-the-browser-with-tensorflowjs) - [ Evaluating AI models for code comprehension](https://www.wearedevelopers.com/videos/1462-evaluating-ai-models-for-code-comprehension) - [Overview of Machine Learning in Python](https://www.wearedevelopers.com/videos/840-overview-of-machine-learning-in-python) - [Streaming AI Responses in Real-Time with SSE in Next.js & NestJS](https://www.wearedevelopers.com/videos/1630-streaming-ai-responses-in-real-time-with-sse-in-next-js-nestjs) - [Outclassing Frontier LLMs at Extracting Information](https://www.wearedevelopers.com/videos/100303-outclassing-frontier-llms-at-extracting-information) ## Related Articles - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models) - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production) - [Top Big Data Technologies That You Need to Know](https://www.wearedevelopers.com/magazine/108-top-big-data-technologies-that-you-need-to-know) - [13 AI Tools You Have to Try](https://www.wearedevelopers.com/magazine/219-13-ai-tools-you-have-to-try) - [MLOps – What’s the deal behind it?](https://www.wearedevelopers.com/magazine/125-mlops-what-s-the-deal-behind-it) - [Graph and AI Trends 2026: Why Is AI Running but Not Yet Delivering?](https://www.wearedevelopers.com/magazine/680-graph-and-ai-trends-2026-why-is-ai-running-but-not-yet-delivering)