San Jose, CA (Hybrid)
Contract | Full-Time | Day Shift (MF)
$50/hr | 1 Year (Potential Extension)
Were seeking a talented and motivated Associate Fraud Risk Data Scientist to join a leading fintech company's Risk Data & AI Innovation team. This role focuses on fraud detection, risk analysis, and loss mitigation through advanced data science and machine learning.
The ideal candidate thrives in ambiguity, enjoys solving complex problems, and can translate analytical insights into scalable fraud prevention solutions.
Design, develop, and deploy machine learning and AI models to detect and mitigate fraud.
Partner with product and engineering teams to implement, monitor, and refine AI solutions.
Collaborate with stakeholders to ensure effective use of models and support risk management initiatives.
Analyze large datasets to identify trends, anomalies, and fraud patterns.
Develop dashboards and visualizations (Tableau, AWS Quicksight) to track key KPIs.
Present findings and recommendations to technical and executive audiences.
2-6 years of experience in machine learning/AI, data science, risk analytics, or fraud analysis within eCommerce, online payments, user trust/risk/fraud, or investigation/product abuse.
Bachelors or Masters degree in Data Science, Data Analytics, Mathematics, Statistics, Data Mining, or related field (or equivalent experience).
Proficiency in SQL, Python, AWS, and Excel (including key data science libraries).
Strong data visualization skills, including Tableau.
Experience working with large datasets.
Excellent communication skills and ability to explain complex results to technical and non-technical stakeholders.
Bonus: Experience with development and implementation of AI tools (LLMs) for risk use cases.
Machine Learning & Artificial Intelligence
Model Development
Dashboard Creation
Project Management