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# Undergraduate Placement - Data Science & Fraud Analytics

- **Company:** LexisNexis Risk Solutions
- **Location:** London, United Kingdom
- **Experience:** Starter
- **Contract:** Internship / Graduate position
- **Skills:** Artificial Intelligence, Data Analysis, Cloud Computing, Data Infrastructure, Data Visualization, Python (Programming Language), Machine Learning, Tensorflow, Microsoft Copilot, Standard Sql, Lexis, Snowflake, Generative AI, Agentic-AI, Information Technology, Cybercrime, Streamlit Framework
- **Published:** October 22, 2026
- **Apply:** https://relx.wd3.myworkdayjobs.com/RiskSolutions/job/London-Wall/Intern_R119888

## About the Role

Are you looking for a paid industrial placement as part of your degree and want to work on problems that genuinely matter?, Love Solving Difficult Problems: You enjoy tackling challenges that don't have obvious answers. You are curious, analytical and willing to experiment, learn and adapt.

Have Strong Analytical Skills: You can interpret data, identify patterns and think critically about business problems.

Are Passionate About Data and Technology: You're excited by the opportunity to work with modern data platforms, cloud technologies and AI tools.

Enjoy Learning New Technologies:

Whether you've used them through university projects, personal projects, hackathons or internships, we'd love to hear about your experience with technologies such as:

 * Python
 * SQL
 * Snowflake
 * dbt
 * Streamlit
 * Machine learning frameworks
 * Generative AI tools
 * Copilot and AI agents
 * Data visualisation platforms

Have an Interest in Fraud, Risk or Cybercrime:

You are interested in understanding how fraud evolves and how analytics, data science and AI can be used to combat increasingly sophisticated threats.

Are Collaborative Team Players:

You enjoy working with others, sharing ideas and contributing to a supportive and inclusive team environment., * Studying a STEM-related degree, including Data Science, Computer Science, Mathematics, Statistics, Physics, Engineering, or another quantitative discipline.

 * Returning to university following the placement year.
 * Right to work in the UK for the duration of the placement., * Experience building applications or dashboards
 * Experience using Snowflake, dbt, Streamlit, machine learning or AI tools
 * Curious exploration of fraud, cybersecurity or risk-related topics

Show us something you've built, analysed, automated or improved. We value practical evidence of learning and problem solving as much as academic achievement.