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Senior Data Scientist II

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  • Company: RELX
  • Location: Brazil
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  • Full Time
  • Brazil
  • Apply on company site
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RELX — company details are preparing and update automatically in a few seconds (or refresh).

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 Risk Solutions division helps organizations manage risk and prevent fraud, and is an equal opportunity employer committed to a fair, accessible hiring process for all candidates.

How to Apply

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Listing facts

  • Role Senior Data Scientist II
  • Employer RELX
  • Location Brazil
  • Type Full Time
  • Posted June 21, 2026
  • Apply by 2026-07-21
  • Country context Brazil
  • Overview Full original description on this page (396 words; rewritten for clarity, not a teaser paste)

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Typical work in Data Scientist

Independent occupational context from O*NET (U.S. public-domain labor data). This is about the occupation, not a rewrite of this employer's posting.

  • 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.

Source: O*NET

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Senior Data Scientist II RELX · Brazil