Senior Data Scientist II

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Occupation tasks (O*NET)

Public-domain labor data — prepare examples for 2–3 of these.

• Analyze, manipulate, or process large sets of data using statistical software.
• Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
• Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
• Clean and manipulate raw data using statistical software.
• Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
• Create graphs, charts, or other visualizations to convey the results of data analysis using specialized software.
• Deliver oral or written presentations of the results of mathematical modeling and data analysis to management or other end users.
• Design surveys, opinion polls, or other instruments to collect data.

O*NET source

Company facts (cached)

Website: relx.com

RELX plc is a British multinational information and analytics company headquartered in London, England. Its businesses provide scientific, technical and medical information and analytics; legal information and analytics; decision-making tools; and organise exhibitions. It operates in 40 countries and serves customers in over 180 nations. It was previously known as Reed Elsevier, and came into being in 1993 as a result of the merger of Reed International, a British trade book and magazine publisher, and Elsevier, a Netherlands-based scientific publisher.

Public cache only — not an employee review.

Role overview (listing rewrite)

RELX, through its LexisNexis Risk Solutions business, is hiring a Senior Data Scientist II in Brazil to shape the future of fraud prevention scoring across Latin America, EMEA, and APAC. This full-time, on-site role blends deep analytical craft with commercial strategy to deliver governed, scalable solutions in digital identity and risk intelligence. About the Role As a Senior Data Scientist II at RELX in Brazil, you will advance our Fraud Prevention Score program and help define next-generation fraud strategies. You'll turn complex analytical work into measurable outcomes, partnering across the business to strengthen risk decisioning and identity intelligence while operating to enterprise governance and Responsible AI standards. Key Responsibilities Own the full lifecycle of fraud prevention models, machine learning systems, and analytical frameworks — from design and build through validation and ongoing monitoring. Steer initiatives behind our Fraud Next Generation roadmap, connecting data science to product, technology, and commercial priorities. Collaborate with Product, Technology, Sales, Pre-Sales, Content Acquisition, and Global Analytics to ship solutions that scale. Surface ways to sharpen fraud detection, entity resolution, identity verification, and data intelligence. Grow Decision Trust offerings through tailored analytics, proofs of concept, customer engagements, and production-ready deployments. Mentor fellow data scientists and champion analytical best practices and shared learning. Keep work aligned with governance standards, Responsible AI principles, and regulatory expectations. Translate findings into clear recommendations for both technical peers and senior leadership. Help shape the long-term analytical roadmap and evaluate new data assets, methods, and emerging technologies. Qualifications Advanced experience in data science, advanced analytics, machine learning, or a related quantitative discipline. Strong grounding in fraud analytics, digital identity, risk modeling, or financial crime prevention. Skilled in predictive modeling, statistical analysis, and large-scale data environments, with a track record of deploying solutions to production. Excellent stakeholder management and communication, with influence across technical and business audiences. Comfortable within global, matrixed organizations, balancing strategy with hands-on execution. Advanced English communication skills required. Exposure to identity intelligence, contributory data ecosystems, fraud platforms, or risk decisioning solutions is highly preferred. About RELX RELX is a global provider of information-based analytics and decision tools. Its LexisNexis…

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Questions to ask them

• What does success look like in the first 90 days for this role?
• How is the team structured, and who would I work with most?
• What tools and systems does this role use daily?
• Is the work primarily based in Brazil, hybrid, or fully remote?