Fraud Detection Data Scientist

Job Title: Fraud Risk Data Scientist Overview: We are seeking a talented, enthusiastic, and dedicated individual to join our Fraud Risk Data Science Team within the Risk Data & AI Innovation organization. In this role, you will support key projects focused on fraud detection, risk analysis, and loss mitigation. The ideal candidate will have hands-on experience with machine learning, advanced AI/ML frameworks, analytics, statistical modeling, and model monitoring. Familiarity with Large Language Models (LLMs) and other AI tools is a strong plus. Key Responsibilities: • Support fraud detection and risk analysis initiatives through data-driven solutions. • Develop and monitor machine learning models using cutting-edge AI/ML frameworks. • Perform statistical analysis and deliver actionable insights to mitigate losses. • Collaborate with technical experts, business partners, and executives to communicate complex results clearly. • Create dashboards and visualizations to present findings (e.g., Tableau). • Drive AI and machine learning projects toward clear business goals and measurable outcomes. Required Skills & Experience: • Experience: 1–3 years in machine learning/AI, data science, risk analytics, or data analysis within industries such as eCommerce, online payments, user trust/risk/fraud, or product abuse investigation. • Education: Bachelor’s or Master’s degree in Data Science, Data Analytics, Mathematics, Statistics, Data Mining, or a related field (or equivalent practical experience). • Strong proficiency in SQL, Python, AWS, Excel, and key data science libraries. • Expertise in data visualization tools (e.g., Tableau). • Experience working with large datasets and applying statistical methods to solve complex business problems. • Ability to communicate technical results effectively to diverse audiences. • Comfortable working in ambiguous environments while driving projects toward actionable outcomes. • Demonstrated analytical thinking and data-driven decision-making skills. Preferred Qualifications: • Experience or aptitude for solving risk-related problems using data science and analytics. • Bonus: Hands-on experience with AI tools (e.g., LLMs) for risk-focused use cases. Compensation: $40-$42/hour