Sobre esta vaga de Senior Data Scientist II na RELX
LexisNexis Risk Solutions is seeking a strategic and business-oriented Senior Data Scientist to drive Fraud Prevention Score initiatives across Brazil, LATAM, EMEA, and APAC.
This role is responsible for advancing analytical capabilities, accelerating fraud prevention innovation, and delivering scalable, governance-driven solutions that support digital identity, risk intelligence, and next-generation fraud strategies.
The ideal candidate combines strong technical expertise with business acumen, stakeholder management, and the ability to translate complex analytical initiatives into measurable business impact.
Key Responsibilities
- Lead the design, development, validation, and monitoring of fraud prevention models, machine learning solutions, and analytical frameworks.
- Drive analytical initiatives supporting Fraud Next Generation strategies, aligning data science capabilities with product, technology, and commercial objectives.
- Partner cross-functionally with Product, Technology, Sales, Pre-Sales, Content Acquisition, and Global Analytics teams to deliver scalable business solutions.
- Identify opportunities to enhance fraud detection, entity resolution, identity verification, and data intelligence capabilities.
- Support the expansion of Decision Trust solutions through customized analytics, proof of concepts, customer engagements, and production-ready implementations.
- Provide technical leadership and mentorship to other data scientists, promoting analytical best practices and knowledge sharing.
- Ensure alignment with enterprise governance standards, Responsible AI principles, and regulatory requirements.
- Communicate analytical findings and recommendations to technical and non-technical stakeholders, including senior leadership.
- Contribute to the long-term analytical roadmap, supporting innovation, product development, and scalable growth initiatives.
- Evaluate new data assets, analytical methodologies, and emerging technologies that can improve fraud prevention performance.
Qualifications
- Advanced experience in Data Science, Advanced Analytics, Machine Learning, or related quantitative fields.
- Strong background in fraud analytics, digital identity, risk modeling, or financial crime prevention.
- Expertise in predictive modeling, machine learning, statistical analysis, and large-scale data environments.
- Experience developing and deploying analytical solutions in production environments.
- Strong stakeholder management and communication skills, with the ability to influence decision-making across technical and business teams.
- Experience working within global and matrixed organizations.
- Ability to balance strategic thinking with hands-on analytical execution.
- Advanced English communication skills required.
- Experience with identity intelligence, contributory data ecosystems, fraud prevention platforms, or risk decisioning solutions is highly preferred.
Professional Profile
- Strategic and business-oriented problem solver.
- Strong technical leader and trusted analytical advisor.
- Collaborative, proactive, and results-driven.
- Comfortable operating in fast-paced, cross-functional, and international environments.
- Passionate about innovation, continuous learning, and delivering measurable business outcomes.
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