Senior Data Scientist II

Remitly•Home based-Illinois, IL

4d•$110,100 - $192,200•Remote

About The Position

LexisNexis Legal & Professional, a part of RELX, is a global provider of information-based analytics and decision tools. The company has a long history of using AI and advanced technologies in the legal market to enhance productivity and transform legal practices. They are deploying ethical and powerful generative AI solutions using a flexible, multi-model approach. The company employs over 2,000 technologists, data scientists, and experts who develop, test, and validate solutions in line with RELX Responsible AI Principles. The Yoda team, a focused division within LexisNexis, manages core datasets related to people, organizations, and taxonomies. These datasets are used internally to build products and deliver customer value. The team is seeking a Data Scientist to advance work in data extraction, data structuring, classification, and analysis. This role is suited for an individual who is versatile, collaborative, and eager to tackle complex problems using NLP, machine learning, large language models, regression, classification, and information retrieval techniques.

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.

Nice To Haves

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.

Responsibilities

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.