Fraud Data Analyst - French Speaking

LexisNexis Risk Solutions
London
2 weeks ago
Create job alert

Fraud Data Analyst - French Speaking


About the Business: LexisNexis Risk Solutions is the essential partner in the assessment of risk. Within our Business Services vertical, we offer a multitude of solutions focused on helping businesses of all sizes drive higher revenue growth, maximize operational efficiencies, and improve customer experience. Our solutions help our customers solve difficult problems in the areas of Anti-Money Laundering/Counter Terrorist Financing, Identity Authentication & Verification, Fraud and Credit Risk mitigation and Customer Data Management. You can learn more about LexisNexis Risk at the link below,risk.lexisnexis.com


About our Team:You will be part of a team of analysts using global data from the largest real-time fraud detection platform to optimise solutions for our enterprise customers.


About the Role:You will use your experience with data analysis to investigate suspicious behavior. This will provide new insights to customers leading to immediate real-world impact in the form of lower customer friction, reduced fraud losses and as a result, increased customer profitability.

You’ll leverage a real-time platform analyzing billions of transactions per month for some of the largest companies operating in Financial Services, Insurance, e-Commerce, and On-Demand Services. These tools will allow you to attain a unique perspective of the Internet and every persona connected to it. You’ll be continually collaborating with internal product and engineering teams, customer-facing account teams, and external business leaders and risk managers. The comprehensive policy you build will go head-to-head against some of the most motivated attackers in the world to protect billions in revenue.


Responsibilities

  • Conducting in-depth reviews of complex fraud cases. identifying trends and actionable insights, documenting your findings and making clear recommendations on how to mitigate risk
  • Using your SQL and Python skills to increase our customers’ fraud capture. While reducing false positives, conducting offline analysis of customer data to expose patterns and statistically tune policies. Produce executive-level reports and own the end-to-end delivery of your recommendations by writing rules into the ThreatMetrix® decision engine
  • Building dashboards & reports to track value delivered by the solution. Increasing focus on more bespoke external-facing dashboards that surface the most important insights to each customer
  • Using your excellent attention to detail and ability to craft a story through data. Delivering industry-leading presentations for external and executive audiences with non-technical background
  • Scoping, planning, and delivering customer-focused projects including root cause analysis, reports, dashboards, rule mining and health checks. Demonstrate a professional and customer-centric persona when interacting directly with customers via phone, e-mail, and chat
  • Collaborating with ThreatMetrix teams. Including Products, Engineering, Sales and other Professional Services colleagues around the world to continually redefine best practices


Requirements

  • Experience within a Fraud Strategy or Fraud Analytics function.
  • Proficient in SQL (Python knowledge and BI tools like SuperSet, PowerBI, Tableau a bonus).
  • Experience of working with fraud system management, such as ThreatMetrix, Emailage, Featurespace, Hunter, Iovation, BioCatch, Actimize Falcon, etc.
  • Interest or experience in consulting within the risk, fraud or payments industry.
  • Have attention to detail to ensure quality of project delivery for customers stands out amongst industry peers
  • Track record of building external and executive reports and presentations
  • Have extensive multi-tasking and prioritization skills. Needs to excel in fast paced environment with frequently changing priorities
  • Fluency in French and English language


Learn more about the LexisNexis Risk team and how we workhere

Related Jobs

View all jobs

Python Data Engineer

Python Data Engineer

Python Data Engineer

Python Data Engineer

Python Data Engineer

Python Data Engineer

Get the latest insights and jobs direct. Sign up for our newsletter.

By subscribing you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Rural-Remote Machine Learning Jobs: Finding Balance Beyond the Big Cities

Over the past decade, machine learning (ML) has transformed from a niche research domain into a pervasive technology underpinning everything from recommendation systems and voice assistants to financial forecasting and autonomous vehicles. Historically, the UK’s major tech hubs—particularly London—have been magnets for top ML talent and corporate headquarters. However, remote work has become mainstream, and many ML professionals are realising they can excel in their field while living far beyond the city limits. At MachineLearningJobs.co.uk, we’ve observed a growing interest in positions that allow for a rural lifestyle or a coastal environment, often reflected in search terms like “ML remote countryside” or “tech jobs by the sea.” This surge is no coincidence. Flexible work policies, better rural broadband, and the nature of machine learning tasks—much of which can be done through cloud platforms—are bringing new opportunities to those who wish to swap urban hustle for fresh air and scenic views. Whether you’re a data scientist, ML engineer, researcher, or product manager, a rural or seaside move could reinvigorate your work-life balance. In this article, we’ll unpack why rural-remote ML jobs are on the rise, how you can navigate the challenges of leaving the city, and what you need to do to thrive in a machine learning career beyond the M25. If you’ve dreamt of looking up from your laptop to rolling fields or ocean waves, keep reading—your rural ML role might be closer than you think.

Quantum-Enhanced Machine Learning—Propelling AI into the Next Frontier

Machine learning (ML) has revolutionised how we interpret data, build predictive models, and create intelligent applications. From recommendation engines and self-driving cars to advanced genomics and natural language processing, ML solutions are integral to nearly every corner of modern life. However, as data complexity and model size continue to skyrocket, the computational demands placed on ML systems grow in tandem—often pushing even high-performance classical computers to their limits. In recent years, quantum computing has emerged as a tantalising solution to these challenges. Unlike traditional digital systems, quantum computers exploit quantum mechanics—superposition and entanglement—to process information in ways that defy conventional logic. As these machines mature, they promise exponential speed-ups for certain tasks, potentially reshaping how we approach AI and data-intensive challenges. What does this mean for machine learning? Enter quantum-enhanced ML, a new frontier where quantum processors and classical ML frameworks unite to accelerate model training, tackle high-dimensional data, and solve complex optimisation tasks more efficiently. In this article, we will: Unpack the current state of machine learning, highlighting key bottlenecks. Provide a concise overview of quantum computing—why it’s radical and how it differs from classical technology. Examine potential breakthroughs in quantum-enhanced ML, including real-world use cases and technical approaches. Explore the roles and skill sets that will define this quantum-AI era, with guidance on how to prepare. Discuss the roadblocks (like hardware maturity and ethical concerns) and how they might be addressed in the years to come. If you’re a machine learning engineer, data scientist, or simply an AI enthusiast fascinated by the next wave of computational innovation, read on—quantum computing could become an integral part of your future toolkit, opening up job opportunities and reimagining what ML can achieve.

Machine Learning Jobs at Newly Funded UK Start-ups: Q3 2025 Investment Tracker

Machine learning (ML) has become the beating heart of modern tech innovation, powering breakthroughs in healthcare, finance, cybersecurity, robotics, and more. Across the United Kingdom, this surge in ML-driven solutions is fueling the success of countless start-ups—and spurring demand for talented machine learning engineers, data scientists, and related professionals. If you’re eager to join a high-growth ML company or simply want to keep tabs on the latest trends, this Q3 2025 Investment Tracker will guide you through the newly funded UK start-ups pushing the boundaries of ML. In this article, we’ll highlight key developments from Q3 2025, delve into the most promising newly funded ventures, and shed light on the machine learning roles they’re urgently seeking to fill. Plus, we’ll show you how to connect with these employers via MachineLearningJobs.co.uk, a dedicated platform for ML job seekers. Let’s dive in!