Senior Data Scientist I

** Please note that the selected individual for this role will be expected to work in our Raleigh, NC location from the time of joining. If you reside outside of the Raleigh region and you are unable or unwilling to relocate, then please consider other roles across our organization that might allow for remote locations. **

Are you looking to develop your Data Scientist experience?
 

Would you enjoy working on our cutting-edge products?
 

About our Team
 

LexisNexis Legal & Professional, which serves customers in more than 150 countries with 11,800 employees worldwide, is part of RELX, 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.

Nexis Solutions, a division of LexisNexis, is seeking a Data Scientist who will focus on search and be dedicated to the creation of next-generation search relevance techniques and strategies for LexisNexis, dramatically improving how our users search and find the answers to their research questions. This role should be able demonstrate versatility, collaborate across teams, and be enthusiastic in tackling new problems as we continue to push technology forward

Responsibilities:

• Working to solve some of the most challenging problems in natural language processing, machine learning, and information retrieval including topical classification, sentiment analysis, user intent detection.

• Research, build, and deploy models based on both shallow and deep machine learning. Train robust NLP-based models a very large corpus of news and financial data

• Apply machine learning techniques for improving search algorithms.

• Drive best practices for NLP/Machine Learning pipelines.

• Maintain current knowledge base of state-of-the-art ML algorithms (BERT, ELMo, GPT, etc.), API's, and open-source methods, able to quickly evaluate alternatives

• Translate complex business requirements into actionable stories with reasonable time estimates.

• Work with product leaders to apply data science solutions.

Requirements:
 

• In-depth understanding of machine learning techniques such as classification, clustering, recommendation systems, and statistical models.

• Experience using Machine Learning and associated packages like scikit-learn, pandas, NumPy.

• Proficiency training large scale models in at least one modern deep learning engine such as TensorFlow, Keras, PyTorch/Torch, MXNet, Caffe/Caffe2

• Min 5 years of experience using NLP tools and methods such as OpenNLP, Stanford NLP, LDA, Gensim, spaCy

• Min 5 years recent coding experience using Python AND/OR (Java OR Scala)

• SQL programming experience

• Experience and ability to design and work within complex data models.

• Strong skills in setting, communicating, implementing, and achieving business objectives and goals

• Familiarity with Cloud-based Machine Learning environments, Spark, Visualization/Dashboarding, Elasticsearch, Solr, Graph DBs (i.e., Janus Graph, Neptune, etc.)

• Able to work well on a Small Team and Lead other more Jr members of the team

LexisNexis, a division of RELX, is 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. 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: https://forms.office.com/r/eVgFxjLmAK , or please contact 1-855-833-5120.

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