Senior Data Scientist II

LexisNexis Risk Solutions; Illinois; Hybrid; USD 110,100 - 183,500; Full time

Benefits offered by this job

Flexible working hours

Wellbeing initiatives

Shared parental leave

Study assistance

Sabbaticals

Job summary

LexisNexis Risk Solutions is seeking a Data Scientist to enhance their team. The role involves tackling challenges in natural language processing and machine learning, developing models, and translating business objectives into actionable plans.

The ideal candidate will possess at least 5 years of coding expertise, especially in Python, and experience with various machine learning frameworks. The position offers flexible working hours and numerous employee wellbeing initiatives.

Compensation ranges from $110,100 to $183,500, with additional bonuses based on performance.

Qualifications

• Strong understanding of machine learning techniques across various models.
• Experience with Python data science libraries and NLP tools.
• Proficiency in training large-scale models and cloud deployments.

Responsibilities

• Solve problems in NLP, machine learning, and data retrieval.
• Research, build, and deploy machine learning models.
• Partner with teams to solve real business problems.

Skills

Machine learning techniques

Python libraries (scikit-learn, pandas)

NLP tools (spaCy, OpenNLP)

Deep learning frameworks (TensorFlow, PyTorch)

SQL programming

Data model design

Education

5+ years coding experience in Python or Java/Scala

Tools

Cloud services (AWS)

Visualization tools

Graph databases (JanusGraph, Neptune)

Job description

About the Yoda Team

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.

Job Overview

We are looking for a Data Scientist to join our team and help advance our work in data extraction, data structuring, classification, and analysis.

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.

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.

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.

Benefits

We promote a healthy work/life balance across the organisation, offering numerous wellbeing initiatives, shared parental leave, study assistance, and sabbaticals. Working pattern: flexible hours to fit your productivity.

Compensation

Base Pay Range: Home based-Illinois $110,100 - $183,500. If performed in Chicago, IL, the base pay range is $115,400 - $192,200. Eligible for an annual incentive bonus.

EEO Statement

We are 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. USA Job Seekers: EEO Know Your Rights.