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# Expert Data Scientist

- **Company:** Experian Information Solutions, Inc.
- **Location:** United States (Remote available)
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Business Analytics Applications, Data Analysis, Big Data, Computer Programming, Python (Programming Language), Machine Learning, SQL Databases, Computational Statistics, Large Language Models, Generative AI, Agentic-AI, Data Strategy, Information Technology
- **Published:** November 12, 2026
- **Apply:** https://startup.jobs/expert-data-scientist-ai-fraud-applications-experian-10752880

## About the Role

* Master's degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, Economics, or a related quantitative discipline, or equivalent relevant experience.
 * 5+ years of professional experience in data science, machine learning, statistical modeling, or advanced analytics consistent with a senior-level role.
 * Hands-on programming experience with Python and SQL.
 * Experience developing and evaluating statistical or machine-learning solutions using large datasets.
 * Experience translating business problems into analytical solutions, models, proofs of concept, or prototypes.
 * Experience in financial services, e-commerce, fraud, identity, credit risk, decisioning, or other data-intensive digital environments.
 * Experience developing prototypes, analytical tools, or new capabilities beyond traditional model development.
 * Exposure to generative AI, LLMs, AI agents, or other new AI technologies
 * Experience with modern cloud analytics platforms.
 * #LI-Hybrid

## Description

You will work across Analytics, Product, and Engineering to identify opportunities, shape the data strategy needed to support them, develop and evaluate new approaches, and help move promising concepts from idea to prototype. This is an individual contributor position and you will report into the Sr. Manager of Fraud Analytics

What You'll Do

 * Apply advanced statistical, machine-learning, and analytical techniques to complex business problems.
 * Translate ambiguous business problems into structured hypotheses, experiments, models, and prototypes.
 * Identify new opportunities where data science and new AI technologies can create value.
 * Help shape data strategy for new analytics and AI capabilities by identifying the data, derived features, and data assets needed to support experimentation, development, and scalable solutions.
 * Prototype and evaluate new approaches, comparing them with existing methods and identifying both strengths and failure modes.
 * Develop evaluation criteria covering model or solution quality, reliability, value, operational practicality, and risk.
 * Partner with Product, Engineering, and business teams to move promising analytical concepts toward practical applications.
 * Stay current with new technologies, including generative and agentic AI, and evaluate their applicability to business problems.
 * Share insights, mentor junior members of the team and help build a culture of experimentation, innovation, and learning.